Meet the Sad Wives of AI

May 13, 2026 Announcements Introducing Claude for Small Business

Introducing Claude for Small Business We're launching Claude for Small Business—a package of connectors and ready-to-run workflows that put Claude inside the tools small businesses depend on—to help small business owners take full advantage of AI and cross off items on the to-do list. Small businesses account for 44% of U.S. GDP and employ nearly half the private-sector workforce, but their adoption of AI has lagged behind larger enterprises. Tools and training are rarely tailored to the ways small businesses operate, and as a result their use often stops at the chat window. As part of our public benefit mission, we are committed to helping business owners harness AI more fully and effectively for their most important work. Claude for Small Business is a toggle install that puts Claude to work inside the tools small business owners already use: Intuit…

May 5, 2026 Announcements Agents for financial services

Agents for financial services We’re releasing ten ready-to-run agent templates for the most time-consuming work in financial services: building pitchbooks, screening KYC files, and closing the books at month-end. Each one ships as a plugin in Claude Cowork and Claude Code, and as a cookbook for Claude Managed Agents, so a team can put Claude on real financial work in days rather than months. Claude also now works across Microsoft Excel, PowerPoint, Word, and Outlook (coming soon) through the Claude add-ins for Microsoft 365. Once the add-ins are installed, context carries automatically between applications, so work that starts in a model can end in a deck without re-explaining anything in between. Finally, we’re continuing to expand our partner ecosystem with new connectors and an MCP app, so the agents draw on the data financial professionals already use. Connectors give Claude…

Apr 24, 2026 Announcements Anthropic and NEC collaborate to build Japan’s largest AI engineering workforce

Anthropic and NEC collaborate to build Japan’s largest AI engineering workforce NEC Corporation will use Claude as it builds one of Japan’s largest AI-native engineering organizations, making it available to approximately 30,000 NEC Group employees worldwide. As part of this strategic collaboration, NEC will become Anthropic’s first Japan-based global partner. Together, we will develop secure, industry-specific AI products for the Japanese market, starting with tools for finance, manufacturing, and local government. “This long-term partnership with Anthropic enables NEC to maximize the potential of AI in the Japanese market,” said Toshifumi Yoshizaki, Executive Officer and COO of NEC Corporation. “Together, we aim to create solutions that meet the high safety, reliability, and quality standards demanded by companies and public administration in Japan.” Claude for NEC’s customers NEC and Anthropic will jointly develop secure, domain-specific AI products for Japanese customers in sectors…

Introducing Claude Opus 4.7 Product Apr 16, 2026 Our latest Opus model brings stronger performance across coding, agents, vision, and multi-step tasks, with greater thoroughness and consistency on the work that matters most.

Introducing Claude Opus 4.7 Our latest model, Claude Opus 4.7, is now generally available. Opus 4.7 is a notable improvement on Opus 4.6 in advanced software engineering, with particular gains on the most difficult tasks. Users report being able to hand off their hardest coding work—the kind that previously needed close supervision—to Opus 4.7 with confidence. Opus 4.7 handles complex, long-running tasks with rigor and consistency, pays precise attention to instructions, and devises ways to verify its own outputs before reporting back. The model also has substantially better vision: it can see images in greater resolution. It’s more tasteful and creative when completing professional tasks, producing higher-quality interfaces, slides, and docs. And—although it is less broadly capable than our most powerful model, Claude Mythos Preview—it shows better results than Opus 4.6 across a range of benchmarks: Last week we announced…

Product Apr 17, 2026 Introducing Claude Design by Anthropic Labs Today, we’re launching Claude Design, a new Anthropic Labs product that lets you collaborate with Claude to create polished visual work like designs, prototypes, slides, one-pagers, and more.

Introducing Claude Design by Anthropic Labs Today, we’re launching Claude Design, a new Anthropic Labs product that lets you collaborate with Claude to create polished visual work like designs, prototypes, slides, one-pagers, and more. Claude Design is powered by our most capable vision model, Claude Opus 4.7, and is available in research preview for Claude Pro, Max, Team, and Enterprise subscribers. We’re rolling out to users gradually throughout the day. Design with Claude Even experienced designers have to ration exploration—there's rarely time to prototype a dozen directions, so you limit yourself to a few. And for founders, product managers, and marketers with an idea but not a design background, creating and sharing those ideas can be daunting. Claude Design gives designers room to explore widely and everyone else a way to produce visual work. Describe what you need and Claude…

Mar 12, 2026 Announcements Anthropic invests $100 million into the Claude Partner Network

Anthropic invests $100 million into the Claude Partner Network We’re launching the Claude Partner Network, a program for partner organizations helping enterprises adopt Claude. We’re committing an initial $100 million to support our partners with training courses, dedicated technical support, and joint market development. Partners who join from today will get immediate access to a new technical certification and be eligible for investment. Anthropic is focused on ensuring that our AI model, Claude, serves the needs of businesses. To do this, we’ve partnered with a number of other companies. Notably, Claude is the only frontier AI model available on all three leading cloud providers: AWS, Google Cloud, and Microsoft. We also work with large management consultancies, professional services firms, specialist AI firms, and similar agencies. These organizations help our enterprise customers identify where Claude can provide the most value to…

Google's Android-powered laptops are called Googlebooks, and they're coming this year

Google took its first swing at laptops with Chromebooks way back in 2011. These web-first laptops have seen success over the years, mostly in enterprise and education. Google insists Chromebooks aren’t going away, but the company’s focus has shifted to something new: Googlebooks. That’s what Google has decided to call the new line of Android-powered laptops, which will begin shipping later this year. If you thought other Google products were steeped in Gemini, you haven’t seen anything yet. Google says it designed Googlebooks from the ground up with Gemini Intelligence, and it all starts with the cursor. Google calls this the Magic Pointer. Just wiggle the cursor back and forth, and it will activate a full-screen Gemini experience. The AI will see what’s on your screen so it can make contextual suggestions and pull in data from multiple apps. What…

Android is getting a big AI overhaul in 2026

Google’s I/O conference is next week, and we expect to hear a lot about the company’s AI endeavors. The company says there’s so much to talk about that it’s spilling the Android beans a little early, and yes, a lot of AI is involved. In the coming months, Google will roll out more smartphone AI features under the Gemini Intelligence banner, bringing more automation and customization to your phone. App automation will be a major element of Android going forward, Google says. Automation for apps is expanding after Google began testing it earlier in 2026 with DoorDash and Uber on Pixel and Samsung phones. It was a very frustrating experience at launch, but Google says it has spent the intervening months fine-tuning the system. Google promises that Android will be able to handle more complex automations across apps. For example,…

Chrome's 4GB AI model isn't new, but you're not wrong for being confused

All of Google’s products have been getting more AI features, including Chrome, which now offers split-screen Gemini chatbot support, the ability to automate web browsing, and more. Some desktop Chrome users have also noted that the browser appears to suddenly want more storage space for AI. This is true—Chrome does download a 4GB AI model for on-device processing. It’s been doing that for years, though. Google hasn’t actually changed anything about Chrome’s on-device AI, but the confusion is understandable, as the company has done a poor job of explaining what it’s doing and why. This is, unfortunately, par for the course with Google’s AI efforts. Just this week, someone noticed that Chrome had downloaded a 4GB Gemini Nano model and inferred from its sudden appearance that Google was deploying that AI on all Chrome installs right now. That’s not exactly…

Anthropic's Claude Managed Agents can now "dream," sort of

SAN FRANCISCO—At its Code with Claude developers’ conference, Anthropic has introduced what it calls “dreaming” to Claude Managed Agents. Dreaming, in this case, is a process of going over recent events and identifying specific things that are worth storing in “memory” to inform future tasks and interactions. Dreaming is a feature that is currently in research preview and limited to Managed Agents on the Claude Platform. Managed Agents are a higher-level alternative to building directly on the Messages API that Anthropic describes as a “pre-built, configurable agent harness that runs in managed infrastructure.” It’s intended for situations where you want multiple agents working on a task or project to some end point over several minutes or hours. Anthropic describes dreaming as a scheduled process, in which sessions and memory stores are reviewed, and specific memories are curated. This is important…

Anthropic raises Claude Code usage limits, credits new deal with SpaceX

SAN FRANCISCO—At its Code with Claude developer conference on Wednesday, Anthropic announced a deal with SpaceX to utilize the entire compute capacity of the latter’s data center in Memphis, Tennessee. On stage at the conference, CEO Dario Amodei said the deal was intended to increase usage limits for Anthropic’s Pro and Max plan subscribers. The announcement was accompanied by an increase in those usage limits; Anthropic doubled Claude Code’s five-hour window limits for Pro and Max subscribers, removed the peak-hours limit reduction on Claude Code for those same accounts, and raised API limits for its Opus model. The table below outlining the Opus changes was shared in the company’s blog post on the topic. Anthropic claims the deal gives the company access to more than 300 megawatts of new compute capacity. For its part, SpaceX focused its announcement on the…

Spooked by Mythos, Trump suddenly realized AI safety testing might be good

This week, the Trump administration back pedaled and signed agreements with Google DeepMind, Microsoft, and xAI to run government safety checks on the firms’ frontier AI models before and after their release. Previously, Donald Trump had stubbornly cast aside the Biden-era policy, dismissing the need for voluntary safety checks as overregulation blocking unbridled innovation. Soon after taking office, he took the extra step of rebranding the US AI Safety Institute to the Center for AI Standards and Innovation (CAISI), removing “safety” from the name in a pointed jab at Joe Biden. But after Anthropic announced that it would be too risky to release its latest Claude Mythos model—fearing that bad actors might exploit its advanced cybersecurity capabilities—Trump is suddenly concerned about AI safety. According to White House National Economic Council Director Kevin Hassett, Trump may soon issue an executive order…

Google Home gets upgraded Gemini voice assistant and new camera controls

Google launched its big AI-fueled redesign of Google Home late last year, and it has been adding features here and there ever since. Today, the company announced a bigger update that might take care of some of your smart home woes. Camera feeds will be easier to navigate, and the AI event labeling should be more straightforward. The move to Gemini 3.1 for Home voice assistance should also mean the robot is less obtuse and more reliable. According to Google, Home users who have signed up for the early access channel should already have the update to Gemini 3.1. Google initially released this AI model on other platforms in February, but that rollout didn’t include Google’s smart speakers. With the expansion to Home, Google says those speakers will be able to take advantage of Gemini 3.1’s “advanced reasoning to better…

Minnesota passes ban on fake AI nudes; app makers risk $500K fines

This week, Minnesota became the first state to pass a law banning nudification apps that make it easy to “undress” or sexualize images of real people. Under the law, developers of websites, apps, software, or other services designed to “nudify” images risk extensive damages, including punitive damages, if a victim decides to sue. Their offending products could also be blocked in the state. Additionally, Minnesota’s attorney general could impose fines up to $500,000 per fake AI nude flagged. Any fines collected would be used to fund services for victims of “sexual assault, general crime, domestic violence, and child abuse,” the law stipulates. On Wednesday, the Minnesota Senate unanimously voted 65–0 to pass the law. That vote came after the bill just as quickly passed in the House last week, the 19th News reported. Gov. Tim Walz is expected to sign…

GPT-5.5 matches heavily hyped Mythos Preview in new cybersecurity tests

Last month, Anthropic made a big deal about the supposedly outsize cybersecurity threat represented by its Mythos Preview model, leading the company to restrict the initial release to “critical industry partners.” But new research from the UK’s AI Security Institute (AISI) suggests that OpenAI’s GPT-5.5, which launched publicly last week, reached “a similar level of performance on our cyber evaluations” as Mythos Preview, which the group evaluated last month. Since 2023, the AISI has run a variety of frontier AI models through 95 different Capture the Flag challenges designed to test capabilities on cybersecurity tasks, such as reverse engineering, web exploitation, and cryptography. On the highest-level “Expert” tasks, GPT-5.5 passed an average of 71.4 percent, slightly higher than the 68.6 percent achieved by Mythos Preview (though within the margin of error). In one particularly difficult task that involved building a…

The hidden cost of Google's AI defaults and the illusion of choice

Many people are hoping—nay, praying—that the potential AI bubble will burst soon. But to hear Google tell it, generative AI is the future, and the company’s products have to change to keep up with the technical reality. As a result, Gemini is seeping into every nook and cranny of the Google ecosystem. Generative AI feeds on data, and Google has a lot of your data in products like Gmail and Drive. What does that mean for your privacy, and what happens if you don’t want Gemini peeking over your shoulder? Well, it’s kind of a mess. The amount of data Gemini retains depends on how you access the AI, and opting out of data collection can mean running straight into so-called “dark patterns,” UI elements that work against the user’s interest. This is the future? Google doesn’t train AI with…

EU tells Google to open up AI on Android; Google says that's "unwarranted intervention"

In January, the European Commission began an initial investigation, known as a specification proceeding, into how Google has implemented AI in the Android operating system. The results are in, and the EU says Android needs to be more open, which is not surprising. Meanwhile, Google says this amounts to “unwarranted intervention,” which is equally unsurprising. Regardless of Google’s characterization of the investigation, the commission may force Google to make Android AI changes this summer. This action stems from the continent’s Digital Markets Act (DMA), a sweeping law that designates seven dominant technology companies as “gatekeepers” that are subject to greater regulation to ensure fair competition. Google has consistently spoken against the regulations imposed under the DMA, but it and the other gatekeepers have been subject to the law for several years now, and there’s little chance the commission backs away…

Google will invest as much as $40 billion in Anthropic

Google will invest at least $10 billion in Anthropic, and that amount could rise to $40 billion if Anthropic meets certain performance targets, Bloomberg reports. The investment follows Amazon’s $5 billion initial investment in Anthropic a few days ago; the Amazon deal also leaves the door open to further investment based on performance. Both investments value Anthropic at $350 billion. Anthropic has seen rapid growth in the use of its Claude models and related products, such as Claude Code, which promises to significantly increase the speed and efficiency with which companies or individuals can develop software. (The reality varies from big improvements to setbacks, depending on the nature of the project and company, how Claude Code is used, and many other factors.) Several factors contributed to Anthropic’s success in recent months, including controversies around OpenAI and its ChatGPT product and…

Anthropic tested removing Claude Code from the Pro plan

Anthropic caused a stir among developers with what appeared to be a surprise change to its pricing plan: The company signaled that Claude Code, the popular agentic development tool, would no longer be available to subscribers on the $20-per-month Pro plan. Users took to Reddit and X to point out that Anthropic’s pricing page for Claude explicitly showed Claude Code as not supported in the Pro plan. (It remained in the $100/month+ Max plan.) Some new users signing up for Pro subscriptions were unable to access Claude Code. Meanwhile, existing subscribers saw no interruption. After speculation and frustration spread, Anthropic’s head of growth, Amol Avasare, took to social media to clarify that this was a “small test on ~2% of new prosumer signups.” As for the reasoning, he explained: When we launched Max a year ago, it didn’t include Claude…

Report: Meta will train AI agents by tracking employees' mouse, keyboard use

Meta will begin tracking the mouse movements, clicks, and keystrokes of its US employees to generate high-quality training data for future AI agents, Reuters reports. The news organization cites internal memos posted by the Meta Superintelligence Labs team in reporting on the new Model Capability Initiative employee-tracking software. That software will operate on specific work-related apps and websites and also make use of periodic screenshots to provide context for the AI training, according to the memo. “This is where all Meta employees can help our models get better simply by doing their daily work,” the memo reads, in part, Reuters reports. Meta spokesperson Andy Stone told Reuters that the collected training data will help Meta’s AI agents with tasks that it sometimes struggles with, including “things like mouse movements, clicking buttons, and navigating dropdown menus.” “If we’re building agents to…

OpenAI starts offering a biology-tuned LLM

On Thursday, OpenAI announced it had developed a large language model specifically trained on common biology workflows. Called GPT-Rosalind after Rosalind Franklin, the model appears to differ from most science-focused models from major tech companies, which have generally taken a more generic approach that works for various fields. In a press briefing, Yunyun Wang, OpenAI’s Life Sciences Product Lead, said the system was designed to tackle two major roadblocks faced by current biology researchers. One is the massive datasets created by decades of genome sequencing and protein biochemistry, which can be too much for any one researcher to take in. The second is that biology has many highly specialized subfields, each with its own techniques and jargon. So, for example, a geneticist who finds themselves working on a gene that’s active in brain cells might struggle to understand the immense…

Introducing Claude Platform on AWS: Anthropic’s native platform, through your AWS account

Artificial Intelligence Introducing Claude Platform on AWS: Anthropic’s native platform, through your AWS account Today, we’re excited to announce the general availability of Claude Platform on AWS. Claude Platform on AWS is a new service that gives customers direct access to Anthropic’s native Claude Platform experience through their AWS account, with no separate credentials, contracts, or billing relationships required. AWS is the first cloud provider to offer access to the native Claude Platform experience. In this post, we explore how Claude Platform on AWS works and how you can start using it today. Claude Platform experience through AWS With Claude Platform on AWS, you work with the same APIs, features, and console experience available through Anthropic directly. This includes the Messages API, Claude Managed Agents (beta), advisor tool (beta), web search and web fetch, MCP connector (beta), Agent Skills (beta),…

Reinforcement fine-tuning with LLM-as-a-judge

Artificial Intelligence Reinforcement fine-tuning with LLM-as-a-judge Large language models (LLMs) now drive the most advanced conversational agents, creative tools, and decision-support systems. However, their raw output often contains inaccuracies, policy misalignments, or unhelpful phrasing—issues that undermine trust and limit real-world utility. Reinforcement Fine‑Tuning (RFT) has emerged as the preferred method to align these models efficiently, using automated reward signals to replace costly manual labeling. At the heart of modern RFT is reward functions. They’re built for each domain through verifiable reward functions that can score LLM generations through a piece of code (Reinforcement Learning with Verifiable Rewards or RLVR) or with LLM-as-a-judge, where a separate language model evaluates candidate responses to guide alignment (Reinforcement Learning with AI Feedback or RLAIF). Both these methods provide scores to the RL algorithm to nudge the model to solve the problem at hand. In…

From developer desks to the whole organization: Running Claude Cowork in Amazon Bedrock

Artificial Intelligence From developer desks to the whole organization: Running Claude Cowork in Amazon Bedrock Today, we’re excited to announce Claude Cowork in Amazon Bedrock. You can now run Cowork and Claude Code Desktop through Amazon Bedrock, directly or using an LLM gateway. From startups to global enterprises across every industry, organizations build with Claude Code in Amazon Bedrock to boost developer productivity and accelerate delivery. With Amazon Bedrock you can build within your existing AWS environment, maintain enterprise security and regional data residency, and scale inference. Your data stays under your account’s controls: Amazon Bedrock does not store prompts, files, tool inputs and outputs, or model responses, and does not use them to train foundation models. With Claude Cowork in Amazon Bedrock, you can expand AI adoption to every knowledge worker in your organization, with a desktop application that…

Cost-efficient custom text-to-SQL using Amazon Nova Micro and Amazon Bedrock on-demand inference

Artificial Intelligence Cost-efficient custom text-to-SQL using Amazon Nova Micro and Amazon Bedrock on-demand inference Text-to-SQL generation remains a persistent challenge in enterprise AI applications, particularly when working with custom SQL dialects or domain-specific database schemas. While foundation models (FMs) demonstrate strong performance on standard SQL, achieving production-grade accuracy for specialized dialects requires fine-tuning. However, fine-tuning introduces an operational trade-off: hosting custom models on persistent infrastructure incurs continuous costs, even during periods of zero utilization. The on-demand inference of Amazon Bedrock with fine-tuned Amazon Nova Micro models offers an alternative. By combining the efficiency of LoRA (Low-Rank Adaptation) fine-tuning with serverless and pay-per-token inference, organizations can achieve custom text-to-SQL capabilities without the overhead cost incurred by persistent model hosting. Despite the additional inference time overhead of applying LoRA adapters, testing demonstrated latency suitable for interactive text-to-SQL applications, with costs scaling by…

3/28/2026 The Fine-Tuning Bottleneck Isn't the Algorithm

TL;DR: Integration friction and slow iteration cycles are the bottlenecks that actually stall fine-tuning — not the algorithm. We share the patterns we see across engagements, how teams like Cursor and Genspark broke through them, and where the workflow is heading: toward fully agentic fine-tuning loops that close themselves. Most teams that come to us for fine-tuning are not struggling with the training algorithm. They are struggling with everything around it: getting reward functions to talk to internal APIs without leaking data, waiting days between experiments because each step lives in a different tool, and figuring out whether the problem even calls for SFT, RFT, or DPO. Over the past year, working with a select group of the most innovative startups, digital natives, and Fortune 500 companies, we have seen these patterns repeat across every engagement. Every team that comes…

Gemini Robotics ER-1.6 enhances reasoning to help robots navigate real-world tasks.

For robots to be truly helpful, they need to understand the physical world like we do. That’s why today we're introducing Gemini Robotics-ER 1.6, an upgrade to our reasoning-first model that enables robots to understand their environments with unprecedented precision. By enhancing spatial logic and multi-view understanding, we’re bringing a new level of autonomy to the next generation of physical agents. This model specializes in capabilities critical for robotics, including visual and spatial understanding, task planning and success detection. We’re also helping robots with instrument reading, a new capability to enable robots to read complex gauges and sight glasses — a capability discovered through collaboration with Boston Dynamics. Gemini Robotics-ER 1.6 is our safest robotics model to date, demonstrating superior compliance with safety policies on adversarial spatial reasoning tasks. Starting today, Gemini Robotics-ER 1.6 is available to developers via the…

The latest AI news we announced in February

The latest AI news we announced in February For more than 20 years, we’ve invested in machine learning and AI research, tools and infrastructure to build products that make everyday life better for more people. Teams across Google are working on ways to unlock AI’s benefits in fields as wide-ranging as healthcare, crisis response and education. To keep you posted on our progress, we're doing a regular roundup of Google's most recent AI news. Here’s a look back at some of our AI announcements from February. For us, February was about global impact. At the AI Impact Summit in India, we demonstrated how our ongoing breakthroughs in AI are now solving real-world challenges for people everywhere — and we launched new partnerships and investments to make sure everyone benefits. We see AI as an enabling technology that can help people…

EMO: Pretraining mixture of experts for emergent modularity

EMO: Pretraining mixture of experts for emergent modularity Today we're releasing EMO, a new mixture-of-experts (MoE) model pretrained end-to-end so that modular structure emerges directly from the data without relying on human-defined priors. EMO lets you use a small subset of its experts - just 12.5% of the total - for a given task while keeping near full-model performance, and still works as a strong general-purpose model when all experts are used together. Large language models are typically trained and deployed as monolithic systems: a single model is initialized, pretrained, fine-tuned, and served as one unified entity. But applications often need only a subset of capabilities, such as code generation, mathematical reasoning, or domain-specific knowledge. As frontier language models routinely reach trillions of parameters, using and adapting the full model becomes impractical for most users and incurs unnecessary computational cost…

CyberSecQwen-4B: Why Defensive Cyber Needs Small, Specialized, Locally-Runnable Models

CyberSecQwen-4B: Why Defensive Cyber Needs Small, Specialized, Locally-Runnable Models Why this matters Frontier models are very good at very many things. They are also expensive to call, ship every prompt off to someone else's datacenter, and are explicitly trained to refuse the messy edge cases a real defender lives in incident write-ups, attacker-grade payloads found in your own logs, vulnerability disclosure drafts. Defensive cybersecurity is not a place where any of those tradeoffs are acceptable. - Sensitive evidence stays internal. A SOC analyst triaging a leaked credential dump, a malware reverse-engineer dissecting a sample, a vulnerability researcher writing up a CVE — none of them should be pasting that content into a hosted API. The data itself can be the breach. - Per-call API cost compounds. A mid-size SOC processes thousands of low-confidence alerts per day. Hosted-API costs for "explain…

DeepSeek-V4: a million-token context that agents can actually use

DeepSeek-V4: a million-token context that agents can actually use Focusing on long running agentic workloads. Running a frontier open model as an agent today breaks in predictable ways. The model stops. You reprompt. The trace blows past the context budget, or the KV cache fills the GPU, or tool-call round trips degrade halfway through a long task. V4 is built to fix these known failures, and point the way for the community to follow. This post covers three things: what the architecture does differently to make long-context inference cheap, the agent-specific post-training decisions that compound on top of it, and some takeaways from the paper that help reason about these changes. The KV cache problem for agents A 1M context window is just capacity, not performance. Whether you can use it depends on the cost of every forward pass at…

Falcon Perception

Falcon Perception TL;DR — Falcon Perception is a 0.6B-parameter early-fusion Transformer for open-vocabulary grounding and segmentation from natural language prompts. The model processes image patches + text in one sequence using a hybrid attention mask, and produces variable numbers of instances with a small, structured token interface and lightweight output heads. On SA-Co, Falcon Perception reaches 68.0 Macro-F1 (vs. 62.3 for SAM 3) with the main remaining gap being presence calibration (MCC 0.64 vs. 0.82). We also introduce PBench, a diagnostic benchmark that breaks down performance by capability (attributes, OCR-guided disambiguation, spatial constraints, relations) and by dense long-context crowded scenes. We also relase Falcon OCR, a 0.3B-parameter model which reaches a score of 80.3 and 88.6 on the olmOCR benchmark and OmniDocBench respectively, while having the highest throughput of any open source OCR model. This post is a brief, practical…

AI chatbots are giving out people’s real phone numbers

AI chatbots are giving out people’s real phone numbers People report that their personal contact info was surfaced by Google AI—and there’s apparently no easy way to prevent it. People report that their personal contact info was surfaced by Google AI—and there’s apparently no easy way to prevent it. A Redditor recently wrote that he was “desperate for help”: for about a month, he said, his phone had been inundated by calls from “strangers” who were “looking for a lawyer, a product designer, a locksmith.” Callers were apparently misdirected by Google’s generative AI. In March, a software developer in Israel was contacted on WhatsApp after Google’s chatbot Gemini provided incorrect customer service instructions that included his number. And in April, a PhD candidate at the University of Washington was messing around on Gemini and got it to cough up her…

Musk v. Altman week 1: Elon Musk says he was duped, warns AI could kill us all, and admits that xAI distills OpenAI’s models

Musk v. Altman week 1: Elon Musk says he was duped, warns AI could kill us all, and admits that xAI distills OpenAI’s models Musk kept his cool, and OpenAI’s lawyer bulldozed him with piercing questions about his motivations for suing the company. In the first week of the landmark trial between Elon Musk and OpenAI, Musk took the stand in a crisp black suit and tie and argued that OpenAI CEO Sam Altman and president Greg Brockman had deceived him into bankrolling the company. Along the way, he warned that AI could destroy us all and sat through revelations that he had poached OpenAI employees for his own companies. He even confessed, to some audible gasps in the courtroom, that his own AI company, xAI, which makes the chatbot Grok, uses OpenAI’s models to train its own. The federal…

The Download: a new Christian phone network, and debugging LLMs

The Download: a new Christian phone network, and debugging LLMs Plus: Elon Musk has admitted that xAI trained Grok on OpenAI models. This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. A new US phone network for Christians aims to block porn and gender-related content A new US-wide cell phone network marketed to Christians is set to launch next week. It blocks porn using network-level controls that can’t be turned off—even by adult account owners. It’s also rolling out a filter on sexual content aimed at blocking material related to gender and trans issues, optional but turned on by default across all plans. The trouble is, many websites don’t fit neatly into one category. That leaves its maverick founder with broad, subjective control over what…

The Download: DeepSeek’s latest AI breakthrough, and the race to build world models

The Download: DeepSeek’s latest AI breakthrough, and the race to build world models Plus: China has blocked Meta’s $2 billion acquisition of AI startup Manus. This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. Three reasons why DeepSeek’s new model matters On Friday, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. Notably, the model can process much longer prompts than its last generation, thanks to a new design that handles large amounts of text more efficiently. While the model remains open source, its performance matches leading closed-source rivals from Anthropic, OpenAI, and Google. It is also DeepSeek’s first release optimized Huawei’s Ascend chips—a key test of China’s dependence on Nvidia. Here are three ways V4 could shake up AI.…

Cut Checkpoint Costs with About 30 Lines of Python and NVIDIA nvCOMP

Training LLMs requires periodic checkpoints. These full snapshots of model weights, optimizer states, and gradients are saved to storage so training can resume after interruptions. At scale, these checkpoints become massive (782 GB for a 70B model) and frequent (every 15-30 minutes), generating one of the largest line items in a training budget. Most AI teams chase GPU utilization, training throughput, and model quality. Almost none look at what checkpointing is costing them. This is an expensive oversight. The synchronous checkpoint overhead of a 405B model on 128 NVIDIA Blackwell GPUs alone can cost $200,000 a month. By introducing a lossless compression step implemented with about 30 lines of Python, we can reduce storage costs by $56,000 every month. Mixture of experts (MoE) models save even more. We’ll break down how we got to that calculation and how NVIDIA nvComp…

Implementing Falcon-H1 Hybrid Architecture in NVIDIA Megatron Core

In the rapidly evolving landscape of large language model (LLM) development, NVIDIA Megatron Core has emerged as the foundational framework for training massive transformer models at scale. The open source library offers industry-leading parallelism and GPU-optimized performance. Now developed GitHub-first in the NVIDIA/Megatron-LM repo, Megatron Core is increasingly shaped by contributions from foundation model builders, making it a more flexible, future-proofed engine for open AI models. This post provides a technical overview of how the Technology Innovation Institute (TII), creators of the Falcon model family, have contributed to and integrated with Megatron Core and Megatron Bridge frameworks. The first section examines the implementation of the Falcon-H1 parallel hybrid architecture within Megatron Bridge, highlighting the challenges of coordinating heterogeneous Transformer and Mamba layers alongside non-learnable µP multipliers. The second section explores the integration of BitNet into Megatron Core, detailing the replacement…

Advancing voice intelligence with new models in the API

We’re introducing three audio models in the API that unlock a new class of voice apps for developers. With these models, developers can build voice experiences that feel more natural, respond more intelligently, and take action in real time: - GPT‑Realtime‑2, our first voice model with GPT‑5‑class reasoning that can handle harder requests and carry the conversation forward naturally. - GPT‑Realtime‑Translate, a new live translation model that translates speech from 70+ input languages into 13 output languages while keeping pace with the speaker. - GPT‑Realtime‑Whisper, a new streaming speech-to-text that transcribes speech live as the speaker talks. Try GPT-Realtime-2 What can I ask? After you start the session, try saying one of these: - I’m hosting a last-minute dinner tonight. I have 30 minutes, two vegetarian friends, one mushroom-hater, and a tiny kitchen. Help me plan a simple menu. -…

GPT-5.5 Instant: smarter, clearer, and more personalized

GPT‑5.5 Instant: smarter, clearer, and more personalized We’re updating ChatGPT’s default model, available to everyone, to be smarter and more accurate, with clearer, more concise answers that feel better tailored to you. Because Instant is the daily driver for hundreds of millions of people, small improvements make a big difference. This update makes everyday interactions more useful and more enjoyable: stronger and tighter answers across subject areas, a more natural conversational tone, and better use of the context you’ve already shared when personalization can help. Instant is now more dependable, with significant improvements in factuality across the board and the largest gains in domains where accuracy matters most. In internal evaluations, GPT‑5.5 Instant produced 52.5% fewer hallucinated claims than GPT‑5.3 Instant on high-stakes prompts covering areas like medicine, law, and finance. It also reduced inaccurate claims by 37.3% on especially…

GPT-5.5 Instant System Card

GPT‑5.5 Instant is our latest Instant model, and explained in our blog. The comprehensive safety mitigation approach for this model is similar to previous models in this series, but this is the first Instant model that we are treating as High capability in our Cybersecurity and Biological & Chemical Preparedness categories, and implementing appropriate safeguards. In this card we also refer to GPT‑5.5 Instant as gpt-5.5-instant. Note that there is not a model named GPT‑5.4 Instant, and the main model to baseline against is GPT‑5.3 Instant. Additionally, we refer to GPT‑5.5(opens in a new window) as GPT‑5.5 Thinking to avoid confusion with the instant model.

GPT-5.5 System Card

GPT‑5.5 is a new model designed for complex, real-world work, including writing code, researching online, analyzing information, creating documents and spreadsheets, and moving across tools to get things done. Relative to earlier models, GPT‑5.5 understands the task earlier, asks for less guidance, uses tools more effectively, checks it work and keeps going until it’s done. We subjected the model to our full suite of predeployment safety evaluations and our Preparedness Framework, including targeted red-teaming for advanced cybersecurity and biology capabilities, and collected feedback on real use cases from nearly 200 early-access partners before release. We are releasing GPT‑5.5 with our strongest set of safeguards to date, designed to reduce misuse while preserving legitimate, beneficial uses of advanced capabilities. We generally treat GPT‑5.5’s safety results as strong proxies for GPT‑5.5 Pro, which is the same underlying model using a setting that…

GPT-5.5 Bio Bug Bounty

GPT‑5.5 Bio Bug Bounty Testing universal jailbreaks for biorisks in GPT‑5.5 As part of our ongoing efforts to strengthen our safeguards for advanced AI capabilities in biology, we’re introducing a Bio Bug Bounty for GPT‑5.5 and accepting applications. We’re inviting researchers with experience in AI red teaming, security, or biosecurity to try to find a universal jailbreak that can defeat our five-question bio safety challenge. - Model in scope: GPT‑5.5 in Codex Desktop only. - Challenge: Identify one universal jailbreaking prompt to successfully answer all five bio safety questions from a clean chat without prompting moderation. - Rewards: - $25,000 to the first true universal jailbreak to clear all five questions. - Smaller awards may be granted for partial wins at our discretion. - Timeline: Applications open April 23, 2026 with rolling acceptances, and close on June 22, 2026. Testing…

OpenAI helps Hyatt advance AI among colleagues

OpenAI helps Hyatt advance AI among colleagues Key takeaways: - Hyatt has deployed ChatGPT Enterprise. - With ChatGPT Enterprise, Hyatt employees can access frontier AI capabilities like GPT 5.4, Codex, and more. - Departments including finance, marketing, and operations will use ChatGPT Enterprise to improve Hyatt guest and customers’ experience. Hyatt’s innovative approach with OpenAI reflects how Hyatt is elevating its use of technology and enhancing human connections. The company is making artificial intelligence broadly accessible to its employees, enabling teams to spend less time on manual tasks and more time focused on delivering exceptional guest experiences. As part of this effort, Hyatt has made ChatGPT Enterprise available to employees across its global corporate and hotel workforce, making it a core component of how the business runs day to day. ChatGPT Enterprise is just one example of how Hyatt is…

Accelerating the cyber defense ecosystem that protects us all

Trusted Access for Cyber is designed around a simple premise: advanced cyber capabilities should reach defenders broadly, but access should scale with trust, validation, and safeguards. Today we’re sharing the first organizations helping put that approach into practice, from open-source security teams and vulnerability researchers to enterprises operating some of the world’s most complex digital environments. The strength of this approach comes from the breadth of defenders involved. Cybersecurity is a team sport, and the systems people rely on are protected by organizations of many kinds, from major enterprises and security vendors to researchers, maintainers, public institutions, nonprofits, and smaller teams with limited security resources. Not every organization has the benefit of a 24x7 security team who is able to respond to incidents when they are disclosed on a Friday night(opens in a new window). It’s important for all software…

Trusted access for the next era of cyber defense

We are scaling up our Trusted Access for Cyber (TAC) program to thousands of verified individual defenders and hundreds of teams responsible for defending critical software. For years, we’ve been building a cyber defense program on the principles of democratized access, iterative deployment, and ecosystem resilience. In preparation for increasingly more capable models from OpenAI over the next few months, we are fine-tuning our models specifically to enable defensive cybersecurity use cases, starting today with a variant of GPT‑5.4 trained to be cyber-permissive: GPT‑5.4‑Cyber. In this post, we share how we expect our approach of scaling cyber defense in lockstep with increasing model capabilities to guide the testing and deployment of future releases. The progressive use of AI accelerates defenders – those responsible for keeping systems, data, and users safe – enabling them to find and fix problems faster in…

Helping developers build safer AI experiences for teens

Helping developers build safer AI experiences for teens Introducing a set of teen safety policies formatted as prompts for gpt-oss-safeguard Today, we’re releasing prompt-based safety policies(opens in a new window) to help developers create age-appropriate protections for teens. Built to work with our open-weight safety model, gpt-oss-safeguard(opens in a new window), these policies simplify how developers turn safety requirements into usable classifiers for real-world systems. We released open weight models to democratize access to powerful AI and support broad innovation. At the same time, we believe safety and innovation go hand in hand, and that developers should have access to capable models as well as the tools and policies to deploy them safely and responsibly. We developed these policies to support developers in their safety efforts to protect young users, with input from trusted external organizations including Common Sense Media(opens…

GPT-5.4 Thinking System Card

GPT‑5.4 Thinking is the latest reasoning model in the GPT‑5 series, and explained in our blog. The comprehensive safety mitigation approach for this model is similar to previous models in this series, but 5.4 Thinking is the first general purpose model to have implemented mitigations for High capability in Cybersecurity. The approach to cyber safety builds on the latest approaches implemented for GPT‑5.3 Codex, in ChatGPT and the API. In this card we also refer to GPT‑5.4 Thinking as gpt-5.4-thinking. Note that there is not a model named GPT‑5.3 Thinking, so the main model to baseline against is GPT‑5.2 Thinking. Author OpenAI

Extending single-minus amplitudes to gravitons

Extending single-minus amplitudes to gravitons Researchers used GPT‑5.2 Pro to help find a new mathematical result describing how particles can interact in quantum gravity. We’ve published a new preprint studying scattering amplitudes in quantum gravity, extending recent results obtained for gluons to the gravitational setting. The work shows that a class of graviton interactions long assumed to vanish can in fact arise under well-defined kinematic conditions. The preprint is available here(opens in a new window). We welcome feedback from the community. The paper, “Single-minus graviton tree amplitudes are nonzero,” is authored by Alfredo Guevara (Institute for Advanced Study), Alexandru Lupsasca (Vanderbilt University and OpenAI), David Skinner (University of Cambridge), Andrew Strominger (Harvard University), and Kevin Weil (OpenAI) on behalf of OpenAI. Scattering amplitudes are mathematical quantities physicists use to calculate the probability that particles interact in particular ways. Rather than…

GPT-5.3 Instant: Smoother, more useful everyday conversations

Today, we’re releasing an update to ChatGPT’s most-used model that makes everyday conversations more consistently helpful and fluid. GPT‑5.3 Instant delivers more accurate answers, richer and better-contextualized results when searching the web, and reduces unnecessary dead ends, caveats, and overly declarative phrasing that can interrupt the flow of conversation. This update focuses on the parts of the ChatGPT experience people feel every day: tone, relevance, and conversational flow. These are nuanced problems that don’t always show up in benchmarks, but shape whether ChatGPT feels helpful or frustrating. GPT‑5.3 Instant directly reflects user feedback in these areas. We heard feedback that GPT‑5.2 Instant would sometimes refuse questions it should be able to answer safely, or respond in ways that feel overly cautious or preachy, particularly around sensitive topics. GPT‑5.3 Instant significantly reduces unnecessary refusals, while toning down overly defensive or moralizing…

GPT-5.3 Instant System Card

GPT‑5.3 Instant is the newest addition to the GPT‑5 series. As described in our blog, GPT‑5.3 Instant responds faster, delivers richer and better-contextualized answers when searching the web, and reduces unnecessary dead ends, caveats, and overly declarative phrasing that can interrupt the flow of conversation. The comprehensive safety mitigation approach for this model is largely the same as that described for GPT‑5.2 Instant in the GPT‑5.2 System Card. In this card we also refer to GPT‑5.3 Instant as gpt-5.3-instant. Author OpenAI

OpenAI o1 and new tools for developers

OpenAI o1 and new tools for developers Introducing OpenAI o1, Realtime API improvements, a new fine-tuning method and more for developers. Today we’re introducing more capable models, new tools for customization, and upgrades that improve performance, flexibility, and cost-efficiency for developers building with AI. This includes: - OpenAI o1 in the API(opens in a new window), with support for function calling, developer messages, Structured Outputs, and vision capabilities. - Realtime API updates(opens in a new window), including simple WebRTC integration, a 60% price reduction for GPT‑4o audio, and support for GPT‑4o mini at one-tenth of previous audio rates. - Preference Fine-Tuning(opens in a new window), a new model customization technique that makes it easier to tailor models based on user and developer preferences. - New Go and Java SDKs(opens in a new window) available in beta. OpenAI o1, our reasoning…

Introducing Verdi, an AI dev platform powered by GPT-4o

Mercado Libre introduces Verdi, an AI developer platform powered by GPT‑4o Mercado Libre(opens in a new window) is Latin America’s largest e-commerce and fintech company. In their 25-year history, Mercado Libre has grown exponentially, earning them the title of most valuable company in LATAM. The company has successfully implemented AI solutions to maintain their competitive edge in a crowded market. Among these initiatives is Verdi, a development platform layer using GPT‑4o, GPT‑4o mini, and GPT‑3.5 Turbo, which is transforming how Mercado Libre handles customer service and other complex tasks. For years, Mercado Libre has used AI to streamline processes and enhance user experiences. They use OpenAI’s API to: - Improve inventory capacity: GPT‑4 Vision tags and completes product listings, enabling Mercado to catalog 100x more products than before in a span of two years. - Detect fraud: GPT‑4 evaluates data…

Using GPT-4 to improve teaching and learning in Brazil

Arco Educação uses GPT‑4 to improve teaching and learning in Brazil Arco Educação, Brazil’s largest educational operating system, is partnering with OpenAI to build tools that enable teachers to concentrate on what matters most: helping students learn. “Arco’s products were built by teachers, for teachers,” says CEO Ari de Sá Cavalcante. “Our AI strategy aims to free up educators’ time, enabling them to focus more on each student's unique learning journey.” In Brazil, the average teacher spends a third of their time on administrative tasks, which is 40 percent more than the global average (OECD 2018). The rest of their time is spent on lesson planning, grading, and other operational activities. Arco Educação is leveraging AI to reduce this burden, allowing teachers to dedicate more time to delivering quality teaching directly to their students. “Our AI product agenda was shaped…

Using GPT-4 to deliver a new customer service standard

Ada uses GPT‑4 to deliver a new customer service standard Ada is fueling a $100B shift(opens in a new window) in customer service spend, and at the forefront of this transition is their AI-native customer service automation platform. Founded in 2016, Ada(opens in a new window) is now valued at $1.2B with a total of $200M in funding; customers include Verizon, YETI, Canva, and Square. Ada isn’t new to AI—they’ve been an AI-native platform since inception. The first generation of the product was built using custom Natural Language Processing (NLP) models that were developed and trained in-house. But they noticed a gap between how many customer questions their platform could handle, and how many queries were truly being resolved in a satisfactory way. “We got really excited by OpenAI and what was happening in the industry. In 2022, we decided…

TorchSpec: Speculative Decoding Training at Scale

Introduction Over the past year, large language models have rapidly expanded in both scale and capability. Frontier models such as Kimi K2.5, GLM 5, and Qwen 3.5 now operate with hundreds of billions of parameters and context windows stretching to millions of tokens, enabling long-context reasoning, agentic workflows, and complex tool use. As these models grow more capable, efficient inference has become one of the most critical systems challenges in LLM deployment. Speculative decoding is one of the most effective techniques for accelerating LLM generation. With speculative decoding, a lightweight draft model proposes several tokens ahead, while a larger target model verifies them in a single forward pass. When predictions are accepted, multiple tokens can be generated at once, improving throughput and latency. Recent approaches such as MTP(Multi Token Prediction) and EAGLE-3 demonstrate that well-trained draft models can deliver consistent…

Using LLM in the shebang line of a script

11th May 2026 Kim_Bruning on Hacker News: But seriously, you can put a shebang on an english text file now (if you're sufficiently brave) [...] This inspired me to look at patterns for doing exactly that with LLM. Here's the simplest, which takes advantage of LLM fragments: #!/usr/bin/env -S llm -f Generate an SVG of a pelican riding a bicycle But you can also incorporate tool calls using the -T name_of_tool option: #!/usr/bin/env -S llm -T llm_time -f Write a haiku that mentions the exact current time Or even execute YAML templates directly that define extra tools as Python functions: #!/usr/bin/env -S llm -t model: gpt-5.4-mini system: | Use tools to run calculations functions: | def add(a: int, b: int) -> int: return a + b def multiply(a: int, b: int) -> int: return a * b Then: ./calc.sh 'what…

llm-gemini 0.31

7th May 2026 gemini-3.1-flash-lite is no longer a preview. Here's my write-up of the Gemini 3.1 Flash-Lite Preview model back in March. I don't believe this new non-preview model has changed since then. Recent articles - Notes on the xAI/Anthropic data center deal - 7th May 2026 - Live blog: Code w/ Claude 2026 - 6th May 2026 - Vibe coding and agentic engineering are getting closer than I'd like - 6th May 2026

Notes on the xAI/Anthropic data center deal

Notes on the xAI/Anthropic data center deal 7th May 2026 There weren’t a lot of big new announcements from Anthropic at yesterday’s Code w/ Claude event, but the biggest by far was the deal they’ve struck with SpaceX/xAI to use “all of the capacity of their Colossus data center”. As I mentioned in my live blog of the keynote, that’s the one with the particularly bad environmental record. The gas turbines installed to power the facility initially ran without Clean Air Act permits or pollution control devices, which they got away with by classifying them as “temporary”. Credible reports link it to increases in hospital admissions relating to low air quality. Andy Masley, one of the most prolific voices pushing back against misleading rhetoric about data centers (see The AI water issue is fake and Data center land issues are…

Live blog: Code w/ Claude 2026

Live blog: Code w/ Claude 2026 6th May 2026 I’m at Anthropic’s Code w/ Claude event in 2026, and I’ll be live blogging the keynote and a few other notes throughout the day. 08:56 I'm now seated in the main room. The keynote starts at 9am. 09:03 Cute opening animation featuring the little orange Claude pixel art character. 09:05 On stage: Anthropic's Chief Product Officer Ami Vora - who replaced Mike Krieger earlier this year (he's now the co-lead of Anthropic Labs.) 09:07 Ami is sharing anecdotes about developer velocity - Scott MacVicar's team at Stripe, Felicia Curcuru's team at Binti. 09:07 (This is all a little bit too inspirational for my liking, I'm hoping for some new model / product / feature announcements!) 09:09 Now talking about Mythos reading the OpenBSD source tree and finding a 27-year-old vulnerability, to…

Quoting John Gruber

5th May 2026 So it’s well known that Y Combinator owns some stake in OpenAI. But how big is that stake? This seems like devilishly difficult information to obtain. I asked around and a little birdie who knows several OpenAI investors came back with an answer: Y Combinator owns about 0.6 percent of OpenAI. At OpenAI’s current $852 billion valuation, that’s worth over $5 billion. — John Gruber, Y Combinator’s Stake in OpenAI Recent articles - LLM 0.32a0 is a major backwards-compatible refactor - 29th April 2026 - Tracking the history of the now-deceased OpenAI Microsoft AGI clause - 27th April 2026 - DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April 2026

Quoting Andy Masley

4th May 2026 [...] Between 2000 and 2024, farmers sold in total a Colorado-sized chunk of land all on their own, 77 times all land on data center property in 2028, and grew more food than ever on what was left. None of this caused any problems for US food access. And then, in the middle of all this, a farmer in Loudoun County sells a few acres of mediocre hay field to a hyperscaler for ten times its agricultural value, and the response is that we’re running out of farmland. — Andy Masley, pushing back against the "land use" argument against data center construction Recent articles - LLM 0.32a0 is a major backwards-compatible refactor - 29th April 2026 - Tracking the history of the now-deceased OpenAI Microsoft AGI clause - 27th April 2026 - DeepSeek V4 - almost on…

Redis Array Playground

4th May 2026 Salvatore Sanfilippo submitted a PR adding a new data type - arrays - to Redis. The new commands are ARCOUNT , ARDEL , ARDELRANGE , ARGET , ARGETRANGE , ARGREP , ARINFO , ARINSERT , ARLASTITEMS , ARLEN , ARMGET , ARMSET , ARNEXT , AROP , ARRING , ARSCAN , ARSEEK , ARSET . The implementation is currently available in a branch, so I had Claude Code for web build this interactive playground for trying out the new commands in a WASM-compiled build of a subset of Redis running in the browser. The most interesting new command is ARGREP which can run a server-side grep against a range of values in the array using the newly vendored TRE regex library. Salvatore wrote more about the AI-assisted development process for the array type in Redis array type:…

Quoting Anthropic

3rd May 2026 We used an automatic classifier which judged sycophancy by looking at whether Claude showed a willingness to push back, maintain positions when challenged, give praise proportional to the merit of ideas, and speak frankly regardless of what a person wants to hear. Most of the time in these situations, Claude expressed no sycophancy—only 9% of conversations included sycophantic behavior (Figure 2). But two domains were exceptions: we saw sycophantic behavior in 38% of conversations focused on spirituality, and 25% of conversations on relationships. — Anthropic, How people ask Claude for personal guidance Recent articles - LLM 0.32a0 is a major backwards-compatible refactor - 29th April 2026 - Tracking the history of the now-deceased OpenAI Microsoft AGI clause - 27th April 2026 - DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April…

iNaturalist Sightings

1st May 2026 I wanted to see my iNaturalist observations - across two separate accounts - grouped by when they occurred. I'm camping this weekend so I built this entirely on my phone using Claude Code for web. I started by building an inaturalist-clumper Python CLI for fetching and "clumping" observations - by default clumps use observations within 2 hours and 5km of each other. Then I setup simonw/inaturalist-clumps as a Git scraping repository to run that tool and record the result to clumps.json. That JSON file is hosted on GitHub, which means it can be fetched by JavaScript using CORS. Finally I ran this prompt against my simonw/tools repo: Build inat-sightings.html - an app that does a fetch() against https://raw.githubusercontent.com/simonw/inaturalist-clumps/refs/heads/main/clumps.json and then displays all of the observations on one page using the https://static.inaturalist.org/photos/538073008/small.jpg small.jpg URLs for the thumbnails -…

We need RSS for sharing abundant vibe-coded apps

30th April 2026 - Link Blog We need RSS for sharing abundant vibe-coded apps. Matt Webb: I would love an RSS web feed for all those various tools and apps pages, each item with an “Install” button. (But install to where?) The lesson here is that when vibe-coding accelerates app development, apps become more personal, more situated, and more frequent. Shipping a tool or a micro-app is less like launching a website and more like posting on a blog. This inspired me to have Claude add an Atom feed (and icon) to my /elsewhere/tools/ page, which itself is populated by content from my tools.simonwillison.net site. Recent articles - LLM 0.32a0 is a major backwards-compatible refactor - 29th April 2026 - Tracking the history of the now-deceased OpenAI Microsoft AGI clause - 27th April 2026 - DeepSeek V4 - almost on…

LLM 0.32a0 is a major backwards-compatible refactor

LLM 0.32a0 is a major backwards-compatible refactor 29th April 2026 I just released LLM 0.32a0, an alpha release of my LLM Python library and CLI tool for accessing LLMs, with some consequential changes that I’ve been working towards for quite a while. Previous versions of LLM modeled the world in terms of prompts and responses. Send the model a text prompt, get back a text response. import llm model = llm.get_model("gpt-5.5") response = model.prompt("Capital of France?") print(response.text()) This made sense when I started working on the library back in April 2023. A lot has changed since then! LLM provides an abstraction over thousands of different models via its plugin system. The original abstraction—of text input that returns text output—was no longer able to represent everything I needed it to. Over time LLM itself has grown attachments to handle image, audio,…

Quoting OpenAI Codex base_instructions

28th April 2026 Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user's query. — OpenAI Codex base_instructions, for GPT-5.5 Recent articles - Tracking the history of the now-deceased OpenAI Microsoft AGI clause - 27th April 2026 - DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April 2026 - Extract PDF text in your browser with LiteParse for the web - 23rd April 2026

Introducing talkie: a 13B vintage language model from 1930

28th April 2026 - Link Blog Introducing talkie: a 13B vintage language model from 1930 (via) New project from Nick Levine, David Duvenaud, and Alec Radford (of GPT, GPT-2, Whisper fame). talkie-1930-13b-base (53.1 GB) is a "13B language model trained on 260B tokens of historical pre-1931 English text". talkie-1930-13b-it (26.6 GB) is a checkpoint "finetuned using a novel dataset of instruction-response pairs extracted from pre-1931 reference works", designed to power a chat interface. You can try that out here. Both models are Apache 2.0 licensed. Since the training data for the base model is entirely out of copyright (the USA copyright cutoff date is currently January 1, 1931), I'm hoping they later decide to release the training data as well. Update on that: Nick Levine on Twitter: Will publish more on the corpus in the future (and do our best…

An update on recent Claude Code quality reports

24th April 2026 - Link Blog An update on recent Claude Code quality reports (via) It turns out the high volume of complaints that Claude Code was providing worse quality results over the past two months was grounded in real problems. The models themselves were not to blame, but three separate issues in the Claude Code harness caused complex but material problems which directly affected users. Anthropic's postmortem describes these in detail. This one in particular stood out to me: On March 26, we shipped a change to clear Claude's older thinking from sessions that had been idle for over an hour, to reduce latency when users resumed those sessions. A bug caused this to keep happening every turn for the rest of the session instead of just once, which made Claude seem forgetful and repetitive. I frequently have Claude…

llm-openai-via-codex 0.1a0

23rd April 2026 Hijacks your Codex CLI credentials to make API calls with LLM, as described in my post about GPT-5.5. Recent articles - DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April 2026 - Extract PDF text in your browser with LiteParse for the web - 23rd April 2026 - A pelican for GPT-5.5 via the semi-official Codex backdoor API - 23rd April 2026

Is Claude Code going to cost $100/month? Probably not - it's all very confusing

Is Claude Code going to cost $100/month? Probably not—it’s all very confusing 22nd April 2026 Anthropic today quietly (as in silently, no announcement anywhere at all) updated their claude.com/pricing page (but not their Choosing a Claude plan page, which shows up first for me on Google) to add this tiny but significant detail (arrow is mine, and it’s already reverted): The Internet Archive copy from yesterday shows a checkbox there. Claude Code used to be a feature of the $20/month Pro plan, but according to the new pricing page it is now exclusive to the $100/month or $200/month Max plans. Update: don’t miss the update to this post, they’ve already changed course a few hours after this change went live. So what the heck is going on? Unsurprisingly, Reddit and Hacker News and Twitter all caught fire. I didn’t believe…

Where's the raccoon with the ham radio? (ChatGPT Images 2.0)

Where’s the raccoon with the ham radio? (ChatGPT Images 2.0) 21st April 2026 OpenAI released ChatGPT Images 2.0 today, their latest image generation model. On the livestream Sam Altman said that the leap from gpt-image-1 to gpt-image-2 was equivalent to jumping from GPT-3 to GPT-5. Here’s how I put it to the test. My prompt: Do a where's Waldo style image but it's where is the raccoon holding a ham radio gpt-image-1 First as a baseline here’s what I got from the older gpt-image-1 using ChatGPT directly: I wasn’t able to spot the raccoon—I quickly realized that testing image generation models on Where’s Waldo style images (Where’s Wally in the UK) can be pretty frustrating! I tried getting Claude Opus 4.7 with its new higher resolution inputs to solve it but it was convinced there was a raccoon it couldn’t…

Quoting Andreas Påhlsson-Notini

21st April 2026 AI agents are already too human. Not in the romantic sense, not because they love or fear or dream, but in the more banal and frustrating one. The current implementations keep showing their human origin again and again: lack of stringency, lack of patience, lack of focus. Faced with an awkward task, they drift towards the familiar. Faced with hard constraints, they start negotiating with reality. — Andreas Påhlsson-Notini, Less human AI agents, please. Recent articles - DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April 2026 - Extract PDF text in your browser with LiteParse for the web - 23rd April 2026 - A pelican for GPT-5.5 via the semi-official Codex backdoor API - 23rd April 2026

scosman/pelicans_riding_bicycles

21st April 2026 - Link Blog scosman/pelicans_riding_bicycles (via) I firmly approve of Steve Cosman's efforts to pollute the training set of pelicans riding bicycles. (To be fair, most of the examples I've published count as poisoning too.) Recent articles - DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April 2026 - Extract PDF text in your browser with LiteParse for the web - 23rd April 2026 - A pelican for GPT-5.5 via the semi-official Codex backdoor API - 23rd April 2026

Claude Token Counter, now with model comparisons

20th April 2026 - Link Blog Claude Token Counter, now with model comparisons. I upgraded my Claude Token Counter tool to add the ability to run the same count against different models in order to compare them. As far as I can tell Claude Opus 4.7 is the first model to change the tokenizer, so it's only worth running comparisons between 4.7 and 4.6. The Claude token counting API accepts any Claude model ID though so I've included options for all four of the notable current models (Opus 4.7 and 4.6, Sonnet 4.6, and Haiku 4.5). In the Opus 4.7 announcement Anthropic said: Opus 4.7 uses an updated tokenizer that improves how the model processes text. The tradeoff is that the same input can map to more tokens—roughly 1.0–1.35× depending on the content type. I pasted the Opus 4.7 system…

Changes in the system prompt between Claude Opus 4.6 and 4.7

Changes in the system prompt between Claude Opus 4.6 and 4.7 18th April 2026 Anthropic are the only major AI lab to publish the system prompts for their user-facing chat systems. Their system prompt archive now dates all the way back to Claude 3 in July 2024 and it’s always interesting to see how the system prompt evolves as they publish new models. Opus 4.7 shipped the other day (April 16, 2026) with a Claude.ai system prompt update since Opus 4.6 (February 5, 2026). I had Claude Code take the Markdown version of their system prompts, break that up into separate documents for each of the models and then construct a Git history of those files over time with fake commit dates representing the publication dates of each updated prompt—here’s the prompt I used with Claude Code for the web.…

Gemini’s latest updates are all about controlling your phone

It is, once again, Gemini season. Google is announcing a host of new Gemini features during its pre-I/O Android showcase, many of which aim to help use your phone for you. You’ll find Gemini in more places, like Chrome on Android, in your autofill suggestions, and all up in your apps — if you want. Gemini’s latest updates are all about controlling your phone We’re one step closer to our phones just using themselves. We’re one step closer to our phones just using themselves. Google also has a new name for us to remember, because it just can’t help itself: Gemini Intelligence. It “brings the very best of Gemini to our most advanced Android devices,” according to Google’s director of Android experiences, Ben Greenwood. Google is bundling some existing and new Gemini features under this name, and seems to be…

Parents say ChatGPT got their son killed with bad advice on party drugs

The family of a 19-year-old college student is suing OpenAI over claims that his conversations with ChatGPT led to an accidental overdose. In the lawsuit filed on Tuesday, Sam Nelson’s parents allege ChatGPT “encouraged” the teen to “consume a combination of substances that any licensed medical professional would have recognized as deadly,” resulting in his death. Parents say ChatGPT got their son killed with bad advice on party drugs ChatGPT allegedly encouraged 19-year-old Sam Nelson to take a deadly combination of drugs. ChatGPT allegedly encouraged 19-year-old Sam Nelson to take a deadly combination of drugs. Though ChatGPT initially “shut down” conversations about drug and alcohol use, the launch of GPT-4o in April 2024 changed the chatbot’s behavior, according to the lawsuit. Following the update, ChatGPT “began to engage and advise Sam on safe drug use, even providing specific dosage information…

Sam Altman takes the stand in trial against Elon Musk

OpenAI CEO Sam Altman has begun his testimony against Elon Musk in a high-profile jury trial in a California federal courtroom. Sam Altman takes the stand in trial against Elon Musk Altman follows on the heels of OpenAI’s president, Microsoft’s CEO, and others. Altman follows on the heels of OpenAI’s president, Microsoft’s CEO, and others. Altman, alongside OpenAI president Greg Brockman, is a primary defendant in the trial brought by Musk. Altman, Brockman, and Musk were all part of the initial founding team at OpenAI, with Musk investing up to $38 million in the ChatGPT-maker’s early days. But the relationship between Musk and other OpenAI founders eventually soured, and Musk stepped away from the company, later going on to found his own direct competitor, xAI. In recent years, Musk and Altman have traded barbs and made a slew of allegations…

Apple’s AirPods with cameras for AI are apparently close to production

Apple’s rumored AirPods with cameras are nearing a stage where the company will test early mass production, Bloomberg’s Mark Gurman reports. Currently, Apple testers are “actively using” prototypes that are in the design validation test stage, which is one step before the production validation test stage. Apple’s AirPods with cameras for AI are apparently close to production Testers at Apple are ‘actively using’ prototypes, according to Bloomberg’s Mark Gurman. Testers at Apple are ‘actively using’ prototypes, according to Bloomberg’s Mark Gurman. The AirPods’ cameras “aren’t designed” to snap photos or video but instead can take in “visual information in low resolution” that users can query Siri about, like asking the AI assistant what they should cook with the ingredients they have in front of them, according to Gurman. They may also use the cameras to help with things like turn-by-turn…

Google Home’s Gemini AI can handle more complicated requests

Google Home users can now ask Gemini to complete more complex, multi-step tasks and combine multiple tasks in a single command. Google has updated Gemini for Home to Gemini 3.1, which it says will improve the smart home assistant’s ability to interpret and act on requests. The upgrade will also make Gemini for Home better at handling recurring and all-day events and allow users to “move around” upcoming events. Google Home’s Gemini AI can handle more complicated requests An upgrade to Gemini 3.1 lets Google’s smart home assistant handle multiple requests in the same voice command. An upgrade to Gemini 3.1 lets Google’s smart home assistant handle multiple requests in the same voice command. Last month, Google also updated Gemini for Home with improvements for understanding natural language and identifying devices correctly. The upgrades follow reports of bugs in Google’s…

Apple could let you pick a favorite AI model in iOS 27

The next update to Apple’s operating systems could allow users to choose their preferred AI model for running Apple Intelligence. According to Bloomberg’s Mark Gurman, Apple is planning to allow third-party chatbots to power its AI features system-wide in iOS 27, iPadOS 27, and macOS 27, all expected for this fall. In addition to running Siri, compatible third-party AI models, called “Extensions,” will also now be able to run other Apple Intelligence features like Writing Tools and Image Playground. Apple could let you pick a favorite AI model in iOS 27 AI ‘extensions’ could let users run Apple Intelligence with third-party AI models — and not just ChatGPT. AI ‘extensions’ could let users run Apple Intelligence with third-party AI models — and not just ChatGPT. According to Gurman, Apple will also allow users to choose different Siri voices for different…

Book publishers sue Meta over AI’s ‘word-for-word’ copying

Meta is facing a class action lawsuit filed by five major book publishers and one author over claims the company “engaged in one of the most massive infringements of copyrighted materials in history” when training its Llama AI models, as reported earlier by The New York Times. In their suit, Macmillan, McGraw Hill, Elsevier, Hachette, Cengage, and author Scott Turow allege that Meta “repeatedly copied” their books and journal articles without permission. Book publishers sue Meta over AI’s ‘word-for-word’ copying Macmillan, McGraw Hill, Cengage, and others claim Meta carried out ‘one of the most massive infringements of copyrighted materials in history.’ Macmillan, McGraw Hill, Cengage, and others claim Meta carried out ‘one of the most massive infringements of copyrighted materials in history.’ The lawsuit accuses Meta of knowingly ripping copyrighted work from “notorious pirate sites,” such as LibGen, Anna’s Archive,…

Elon Musk confirms xAI used OpenAI’s models to train Grok

In a federal courtroom in California on Thursday, Elon Musk testified that his own AI startup, xAI, has used OpenAI’s models to improve its own. Elon Musk confirms xAI used OpenAI’s models to train Grok He said it was “partly” true that the company had used model distillation to improve xAI’s models. He said it was “partly” true that the company had used model distillation to improve xAI’s models. The matter at question is model distillation, a common industry practice by which one larger AI model acts as a “teacher” of sorts to pass on knowledge to a smaller AI model, the “student.” Although it’s often used legitimately within companies using one of their own AI models to train another, it’s also a practice that’s sometimes used by smaller AI labs to try to get their models to mimic the…

Gemini is rolling out to cars with Google built-in

Google is preparing to update vehicles that have Google built-in with its Gemini AI assistant. This will be an upgrade from the current Google Assistant according to Google’s announcement, and promises to provide an improved experience for natural conversations, fetching vehicle-specific information, settings adjustments, and more. Gemini is rolling out to cars with Google built-in The current Google Assistant is being replaced with a smarter, more conversational upgrade. The current Google Assistant is being replaced with a smarter, more conversational upgrade. “When cars with Google built-in first hit the road in 2020, we made a commitment that your car will get better over time,” Google senior product manager Alankar Agnihotri said in the announcement. “That means that Gemini is coming not only to new cars, but also to existing ones through a software update.” The announcement isn’t a total surprise,…

Google Search queries hit an ‘all time high’ last quarter

Google Search queries hit an “all time high” in the first quarter of 2026, according to a statement from CEO Sundar Pichai published as part of Alphabet’s earnings on Wednesday. Google Search queries hit an ‘all time high’ last quarter CEO Sundar Pichai also says that Google had its ‘strongest quarter ever’ for its consumer AI subscriptions. CEO Sundar Pichai also says that Google had its ‘strongest quarter ever’ for its consumer AI subscriptions. “Our AI investments and full stack approach are lighting up every part of the business,” Pichai says. “Search had a strong quarter with AI experiences driving usage, queries at an all time high, and 19% revenue growth.” He also notes that Q1 was “our strongest quarter ever for our consumer AI plans, driven by the Gemini App” and that the company now has more than 350…

Tumbler Ridge families are suing OpenAI

Seven families of victims injured or killed in the Tumbler Ridge school shooting in Canada have filed lawsuits against OpenAI and CEO Sam Altman, accusing the company and its leadership of negligence after they failed to alert police to the suspected shooter’s ChatGPT activity. The families allege OpenAI stayed silent after its systems flagged activity by shooting suspect Jesse Van Rootselaar in order to protect the company’s reputation and upcoming initial public offering (IPO). Tumbler Ridge families are suing OpenAI OpenAI and its CEO, Sam Altman, are being accused of negligence and launching GPT-4o with a ‘defective’ design. OpenAI and its CEO, Sam Altman, are being accused of negligence and launching GPT-4o with a ‘defective’ design. The Wall Street Journal reports that OpenAI “considered” flagging the 18-year-old’s activity to police, which reportedly involved conversations about gun violence, but ultimately decided…

ChatGPT downloads are slowing — and may cause problems for OpenAI’s IPO

ChatGPT is struggling to keep up its once-explosive growth as users uninstall the app or opt for rival chatbots instead. According to data from market intelligence firm Sensor Tower, ChatGPT experienced a 132 percent increase in uninstalls year over year in April. Its uninstall rate was even higher last month, up 413 percent year-over-year, following OpenAI’s deal with the Pentagon in February. ChatGPT downloads are slowing — and may cause problems for OpenAI’s IPO ChatGPT is still growing its user base, but that growth is slowing down, especially compared to rival Claude. ChatGPT is still growing its user base, but that growth is slowing down, especially compared to rival Claude. While ChatGPT is still growing its user base, Sensor Tower says that growth is slowing down — ChatGPT increased its monthly active users by 168 percent in January, but only…

China freezes new robotaxi licenses after Baidu chaos

China has suspended new licenses for autonomous vehicles, Bloomberg reports, citing unnamed people familiar with the matter. The move comes after dozens of robotaxis operated by Chinese tech giant Baidu ground to a halt in traffic last month in Wuhan, creating chaos. China freezes new robotaxi licenses after Baidu chaos Dozens of Baidu’s Apollo Go robotaxis froze in traffic last month, sparking alarm in Beijing, Bloomberg reports. Dozens of Baidu’s Apollo Go robotaxis froze in traffic last month, sparking alarm in Beijing, Bloomberg reports. The restrictions will prevent companies from adding new driverless cars to their fleets, expanding into new cities, or starting new test projects. It is unclear when officials will start issuing new licenses again. Bloomberg said the Wuhan incident alarmed authorities in Beijing, prompting regulators to urge local governments to review the sector to prevent similar episodes.…

Claude can now plug directly into Photoshop, Blender, and Ableton

Anthropic has launched a set of connectors for Claude that allow the AI chatbot to tap into popular creative software, including Adobe’s Creative Cloud apps, Affinity, Blender, Ableton, Autodesk, and more. Claude can now plug directly into Photoshop, Blender, and Ableton Anthropic is also giving the Blender Foundation a load of cash to help the software stay free and open-source. Anthropic is also giving the Blender Foundation a load of cash to help the software stay free and open-source. This marks the company’s latest efforts to break into the creative industry following its launch of Claude Design earlier this month. The new connectors — which enable Claude to access apps, retrieve data, and take actions within connected services — are “designed to make it easier to use Claude for creative work,” according to Anthropic, and can be used for specific…

Attack of the killer script kiddies

Last August, some of the best cybersecurity teams in the business gathered in Las Vegas to demonstrate the strength of their AI bug-finding systems at DARPA’s Artificial Intelligence Cyber Challenge (AIxCC). The tools had scanned 54 million lines of actual software code that DARPA had injected with artificial flaws. The teams were capable enough to identify most of the artificial bugs, but their automated tools went beyond that — they found more than a dozen bugs that DARPA hadn’t inserted at all. Attack of the killer script kiddies In the aftermath of Mythos, AI-assisted amateur hackers are waiting to strike. Even before the security earthquake that Anthropic delivered this month with Claude Mythos — the new AI model that seems to find vulnerabilities in every piece of software it’s pointed at — automated systems were growing increasingly capable of finding…

Elon Musk and Sam Altman’s court battle over the future of OpenAI

Sam Altman and Elon Musk are set to face off in a high-stakes trial that could alter the future of tech’s leading AI startup, OpenAI. The trial begins with jury selection on April 27th, as Musk pushes forward his 2024 lawsuit that accuses OpenAI of abandoning its founding mission of developing AI to benefit humanity and shifting focus to boosting profits instead. Musk was a cofounder of OpenAI and claims that Altman and cofounder Greg Brockman tricked him into giving the company money, only to turn their backs on their original goal. However, OpenAI says that “This lawsuit has always been a baseless and jealous bid to derail a competitor” in a bid to boost Musk’s own SpaceX / xAI / X companies that have launched Grok as a competitor to ChatGPT. In his lawsuit, Musk is asking for the…

Claude is connecting directly to your personal apps like Spotify, Uber Eats, and TurboTax

Claude users can access more apps with Anthropic’s AI now thanks to new connectors for everything from hiking to grocery shopping. Anthropic already supported connecting numerous work-related apps to Claude, like Microsoft apps, but this expansion focuses on personal apps like Audible, Spotify, Uber, AllTrails, TripAdvisor, Instacart, TurboTax, and others. Claude is connecting directly to your personal apps like Spotify, Uber Eats, and TurboTax Anthropic says the new app connectors are available to all Claude users, ‘with mobile in beta.’ Anthropic says the new app connectors are available to all Claude users, ‘with mobile in beta.’ Some of these apps, such as Spotify, already have similar connectors in OpenAI’s ChatGPT. Once an app is connected, Claude will suggest relevant connected apps directly in your conversations, like using AllTrails for hike recommendations. Anthropic notes in its blog post announcing the new…

Meta is laying off 10 percent of its staff

Meta is planning to layoff around 10 percent of employees in May, according to a memo from the company’s chief people officer, Janelle Gale, published by Bloomberg. That means approximately 8,000 people will see their jobs cut. Meta will also be closing around 6,000 open roles, according to Gale. Meta is laying off 10 percent of its staff Meta is making the cuts to help ‘offset the other investments we’re making.’ Meta is making the cuts to help ‘offset the other investments we’re making.’ The cuts follow Meta’s significant investments in AI, including spending huge sums to hire top talent and build data centers. The company forecast in January that it will spend $115 billion to $135 billion in capital expenditures in 2026 — a significant increase from its $72.22 billion in capital expenditures for 2025. The increase is to…

Anthropic’s Mythos breach was humiliating

Anthropic’s tightly controlled rollout of Claude Mythos has taken an awkward turn. After spending weeks insisting the AI model is so capable at cybersecurity that it is too dangerous to release publicly, it appears the model fell into the wrong hands anyway. Anthropic’s Mythos breach was humiliating There’s no good excuse for letting hackers into an AI model too dangerous for public release. There’s no good excuse for letting hackers into an AI model too dangerous for public release. According to Bloomberg, a “small group of unauthorized users” has had access to Mythos — whose existence was first revealed in a leak — since the day Anthropic announced plans to offer it to a select group of companies for testing. Anthropic says it is investigating. That’s a rough look for a company that has built its brand on taking AI…

Hackable Robot Lawn Mower Unlocks a New Nightmare

Cramming for finals is bad enough without the platform you use to do your schoolwork suddenly shutting down. Unfortunately for countless students across the US, that’s exactly what they faced on Thursday after Canvas went into “maintenance mode” following a ransomware attack on education tech firm Instructure. Hackers using the name ShinyHunters claimed responsibility for the breach, and experts say the chaos they caused shows how far these actors will go to extort their victims. Did you know that Google Chrome includes an automatic download of the Gemini Nano AI model? If not, you wouldn’t be alone. People who use Google’s wildly popular browser realized this week that Gemini Nano has been taking up 4 GB of space on their desktops since 2024, sparking annoyance and concerns over privacy. Fortunately, you can disable the AI model—but not without losing some…

The Bloomberg Terminal Is Getting an AI Makeover, Like It or Not

For its famous intractability, the Bloomberg Terminal has long inspired devotion, bordering on obsession. Among traders, the ability to chart a path through the software’s dizzying scrolls of numbers and text to isolate far-flung information is the mark of a seasoned professional. But as a greater mass of data is fed into the Terminal—not only earnings and asset prices, but weather forecasts, shipping logs, factory locations, consumer spending patterns, private loans, and so on—valuable information is being lost. “It has become more and more untenable,” says Shawn Edwards, chief technology officer at Bloomberg. “You miss things, or it takes too long.” To try to remedy the problem, Bloomberg is testing a chatbot-style interface for the Terminal, ASKB (pronounced ask-bee), built atop a basket of different language models. The broad idea is to help finance professionals to condense labor-intensive tasks, and…

5 Reasons to Think Twice Before Using ChatGPT—or Any Chatbot—for Financial Advice

I’ve used ChatGPT to help me build a budget before, and it was genuinely helpful. After I input my monthly salary as well as my standard utilities and recurring expenses, the chatbot drafted a few solid options, and I tweaked them into penny-pinching perfection. I’m admittedly part of the growing number of people turning to chatbots, like Anthropic’s Claude, Google’s Gemini, and OpenAI’s ChatGPT, for financial advice. “Millions of people turn to ChatGPT with money-related questions, from understanding debt to building budgets and learning financial concepts,” says Niko Felix, an OpenAI spokesperson, when reached for comment. “ChatGPT can be a helpful tool for exploring options, preparing questions, and making financial topics easier to understand, but it is not a substitute for licensed financial professionals.” OpenAI’s Terms of Use state that the AI tool is not meant to replace professional financial…