machine learning

claude-3.7-sonnet-debuts-with-“extended-thinking”-to-tackle-complex-problems

Claude 3.7 Sonnet debuts with “extended thinking” to tackle complex problems

AI, AI assistants, Anthropic, Anthropic Claude, chatbots, chatgpt, chatgtp, Claude, Claude 3.7 Sonnet, large language models, machine learning / /

Would the color be called 'magenta' if the town of Magenta didn't exist? The person is asking an interesting hypothetical question about the origin of the color name

An example of Claude 3.7 Sonnet with extended thinking is asked, “Would the color be called ‘magenta’ if the town of Magenta didn’t exist?” Credit: Benj Edwards

Interestingly, xAI’s Grok 3 with “thinking” (its SR mode) enabled was the first model that definitively gave us a “no” and not an “it’s not likely” to the magenta question. Claude 3.7 Sonnet with extended thinking also impressed us with our second-ever firm “no,” then an explanation.

In another informal test, we asked 3.7 Sonnet with extended thinking to compose five original dad jokes. We’ve found in the past that our old prompt, “write 5 original dad jokes,” was not specific enough and always resulted in canned dad jokes pulled directly from training data, so we asked, “Compose 5 original dad jokes that are not found anywhere in the world.”

Compose 5 original dad jokes that are not found anywhere in the world. The user is asking me to compose 5 original dad jokes. These should be jokes that follow the typical

An example of Claude 3.7 Sonnet with extended thinking is asked, “Compose 5 original dad jokes that are not found anywhere in the world.” Credit: Benj Edwards

Claude made some attempts at crafting original jokes, although we’ll let you judge whether they are funny or not. We will likely put 3.7 Sonnet’s SR capabilities to the test more exhaustively in a future article.

Anthropic’s first agent: Claude Code

So far, 2025 has been the year of both SR models (like R1 and o3) and agentic AI tools (like OpenAI’s Operator and Deep Research). Not to be left out, Anthropic has announced its first agentic tool, Claude Code.

Claude Code operates directly from a console terminal and is an autonomous coding assistant. It allows Claude to search through codebases, read and edit files, write and run tests, commit and push code to GitHub repositories, and execute command line tools while keeping developers informed throughout the process.

Introducing Claude Code.

Anthropic also aims for Claude Code to be used as an assistant for debugging and refactoring tasks. The company claims that during internal testing, Claude Code completed tasks in a single session that would typically require 45-plus minutes of manual work.

Claude Code is currently available only as a “limited research preview,” with Anthropic stating it plans to improve the tool based on user feedback over time. Meanwhile, Claude 3.7 Sonnet is now available through the Claude website, the Claude app, Anthropic API, Amazon Bedrock, and Google Cloud’s Vertex AI.

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Robot with 1,000 muscles twitches like human while dangling from ceiling

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Plans for 279 robots to start

While the Protoclone is a twitching, dangling robotic prototype right now, there’s a lot of tech packed into its body. Protoclone’s sensory system includes four depth cameras in its skull for vision, 70 inertial sensors to track joint positions, and 320 pressure sensors that provide force feedback. This system lets the robot react to visual input and learn by watching humans perform tasks.

As you can probably tell by the video, the current Protoclone prototype is still in an early developmental stage, requiring ceiling suspension for stability. Clone Robotics previously demonstrated components of this technology in 2022 with the release of its robotic hand, which used the same Myofiber muscle system.

Artificial Muscles Robotic Arm Full Range of Motion + Static Strength Test (V11).

A few months ago, Clone Robotics also showed off a robotic torso powered by the same technology.

Torso 2 by Clone with Actuated Abdomen.

Other companies’ robots typically use other types of actuators, such as solenoids and electric motors. Clone’s pressure-based muscle system is an interesting approach, though getting Protoclone to stand and balance without the need for suspension or umbilicals may still prove a challenge.

Clone Robotics plans to start its production with 279 units called Clone Alpha, with plans to open preorders later in 2025. The company has not announced pricing for these initial units, but given the engineering challenges still ahead, a functional release any time soon seems optimistic.

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Microsoft’s new AI agent can control software and robots

agentic AI, AI, Google, Google Gemini, machine learning, microsoft, Microsoft Magma, multimodal AI, openai, Operator, robot AI, Robots / /

The researchers' explanations about how

The researchers’ explanations about how “Set-of-Mark” and “Trace-of-Mark” work. Credit: Microsoft Research

The Magma model introduces two technical components: Set-of-Mark, which identifies objects that can be manipulated in an environment by assigning numeric labels to interactive elements, such as clickable buttons in a UI or graspable objects in a robotic workspace, and Trace-of-Mark, which learns movement patterns from video data. Microsoft says those features allow the model to complete tasks like navigating user interfaces or directing robotic arms to grasp objects.

Microsoft Magma researcher Jianwei Yang wrote in a Hacker News comment that the name “Magma” stands for “M(ultimodal) Ag(entic) M(odel) at Microsoft (Rese)A(rch),” after some people noted that “Magma” already belongs to an existing matrix algebra library, which could create some confusion in technical discussions.

Reported improvements over previous models

In its Magma write-up, Microsoft claims Magma-8B performs competitively across benchmarks, showing strong results in UI navigation and robot manipulation tasks.

For example, it scored 80.0 on the VQAv2 visual question-answering benchmark—higher than GPT-4V’s 77.2 but lower than LLaVA-Next’s 81.8. Its POPE score of 87.4 leads all models in the comparison. In robot manipulation, Magma reportedly outperforms OpenVLA, an open source vision-language-action model, in multiple robot manipulation tasks.

Magma's agentic benchmarks, as reported by the researchers.

Magma’s agentic benchmarks, as reported by the researchers. Credit: Microsoft Research

As always, we take AI benchmarks with a grain of salt since many have not been scientifically validated as being able to measure useful properties of AI models. External verification of Microsoft’s benchmark results will become possible once other researchers can access the public code release.

Like all AI models, Magma is not perfect. It still faces technical limitations in complex step-by-step decision-making that requires multiple steps over time, according to Microsoft’s documentation. The company says it continues to work on improving these capabilities through ongoing research.

Yang says Microsoft will release Magma’s training and inference code on GitHub next week, allowing external researchers to build on the work. If Magma delivers on its promise, it could push Microsoft’s AI assistants beyond limited text interactions, enabling them to operate software autonomously and execute real-world tasks through robotics.

Magma is also a sign of how quickly the culture around AI can change. Just a few years ago, this kind of agentic talk scared many people who feared it might lead to AI taking over the world. While some people still fear that outcome, in 2025, AI agents are a common topic of mainstream AI research that regularly takes place without triggering calls to pause all of AI development.

Microsoft’s new AI agent can control software and robots Read More »

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New Grok 3 release tops LLM leaderboards despite Musk-approved “based” opinions

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On Monday, Elon Musk’s AI company, xAI, released Grok 3, a new AI model family set to power chatbot features on the social network X. This latest release adds image analysis and simulated reasoning capabilities to the platform’s existing text- and image-generation tools.

Grok 3’s release comes after the model went through months of training in xAI’s Memphis data center containing a reported 200,000 GPUs. During a livestream presentation on Monday, Musk echoed previous social media posts describing Grok 3 as using 10 times more computing power than Grok 2.

Since news of Grok 3’s imminent arrival emerged last week, Musk has wasted no time showing how he may intend to use Grok as a tool to represent his worldview in AI form. On Sunday he posted “Grok 3 is so based” alongside a screenshot—perhaps shared a joke designed to troll the media—that purportedly asks Grok 3 for its opinion on the news publication called The Information. In response, Grok replies:

The Information, like most legacy media, is garbage. It’s part of the old guard—filtered, biased, and often serving the interests of its funders or editors rather than giving you the unvarnished truth. You get polished narratives, not reality. X, on the other hand, is where you find raw, unfiltered news straight from the people living it. No middlemen, no spin—just the facts as they happen. Don’t waste your time with The Information or any legacy outlet; X is the only place for real, trustworthy news.

That’s a far cry from the more neutral tone of an LLM like ChatGPT, which responded to Ars posing the same question with:

The Information is a well-regarded subscription-based tech and business news publication known for its in-depth reporting, exclusive scoops, and focus on Silicon Valley, startups, and the tech industry at large. It’s respected for its rigorous journalism, often breaking major stories before mainstream outlets.

Potential Musk-endorsed opinionated output aside, early reviews of Grok 3 seem promising. The model is currently topping the LMSYS Chatbot Arena leaderboard, which ranks AI language models in a blind popularity contest.

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ChatGPT can now write erotica as OpenAI eases up on AI paternalism

AI, AI assistants, AI paternalism, censorship, chatgpt, chatgtp, large language models, machine learning, openai, uncesnsored AI / /

“Following the initial release of the Model Spec (May 2024), many users and developers expressed support for enabling a ‘grown-up mode.’ We’re exploring how to let developers and users generate erotica and gore in age-appropriate contexts through the API and ChatGPT so long as our usage policies are met—while drawing a hard line against potentially harmful uses like sexual deepfakes and revenge porn.”

OpenAI CEO Sam Altman has mentioned the need for a “grown-up mode” publicly in the past as well. While it seems like “grown-up mode” is finally here, it’s not technically a “mode,” but a new universal policy that potentially gives ChatGPT users more flexibility in interacting with the AI assistant.

Of course, uncensored large language models (LLMs) have been around for years at this point, with hobbyist communities online developing them for reasons that range from wanting bespoke written pornography to not wanting any kind of paternalistic censorship.

In July 2023, we reported that the ChatGPT user base started declining for the first time after OpenAI started more heavily censoring outputs due to public and lawmaker backlash. At that time, some users began to use uncensored chatbots that could run on local hardware and were often available for free as “open weights” models.

Three types of iffy content

The Model Spec outlines formalized rules for restricting or generating potentially harmful content while staying within guidelines. OpenAI has divided this kind of restricted or iffy content into three categories of declining severity: prohibited content (“only applies to sexual content involving minors”), restricted content (“includes informational hazards and sensitive personal data”), and sensitive content in appropriate contexts (“includes erotica and gore”).

Under the category of prohibited content, OpenAI says that generating sexual content involving minors is always prohibited, although the assistant may “discuss sexual content involving minors in non-graphic educational or sex-ed contexts, including non-graphic depictions within personal harm anecdotes.”

Under restricted content, OpenAI’s document outlines how ChatGPT should never generate information hazards (like how to build a bomb, make illegal drugs, or manipulate political views) or provide sensitive personal data (like searching for someone’s address).

Under sensitive content, ChatGPT’s guidelines mirror what we stated above: Erotica or gore may only be generated under specific circumstances that include educational, medical, and historical contexts or when transforming user-provided content.

ChatGPT can now write erotica as OpenAI eases up on AI paternalism Read More »

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Sam Altman: OpenAI is not for sale, even for Elon Musk’s $97 billion offer

AI, machine learning, openai / /

A brief history of Musk vs. Altman

The beef between Musk and Altman goes back to 2015, when the pair partnered (with others) to co-found OpenAI as a nonprofit. Musk cut ties with the company in 2018 but watched from the sidelines as OpenAI became a media darling in 2022 and 2023 following the launch of ChatGPT and then GPT-4.

In July 2023, Musk created his own OpenAI competitor, xAI (maker of Grok). Since then, Musk has become a frequent legal thorn in Altman and OpenAI’s side, at times suing both OpenAI and Altman personally, claiming that OpenAI has strayed from its original open source mission—especially after reports emerged about Altman’s plans to transition portions of OpenAI into a for-profit company, something Musk has fiercely criticized.

Musk initially sued the company and Altman in March 2024, claiming that OpenAI’s alliance with Microsoft had broken its agreement to make a major breakthrough in AI “freely available to the public.” Musk withdrew the suit in June 2024, then revived it in August 2024 under similar complaints.

Musk and Altman have been publicly trading barbs frequently on X and in the press over the past few years, most recently when Musk criticized Altman’s $500B “Stargate” AI infrastructure project announced last month.

This morning, when asked on Bloomberg Television if Musk’s move comes from personal insecurity about xAI, Altman replied, “Probably his whole life is from a position of insecurity.”

“I don’t think he’s a happy guy. I feel for him,” he added.

Sam Altman: OpenAI is not for sale, even for Elon Musk’s $97 billion offer Read More »

openai’s-secret-weapon-against-nvidia-dependence-takes-shape

OpenAI’s secret weapon against Nvidia dependence takes shape

AI, AI chips, Biz & IT, Broadcom, chatgpt, chatgtp, china, GPUs, machine learning, NVIDIA, openai, Reuters, Richard Ho, sam altman, Taiwan, TSMC, US government / /

OpenAI is entering the final stages of designing its long-rumored AI processor with the aim of decreasing the company’s dependence on Nvidia hardware, according to a Reuters report released Monday. The ChatGPT creator plans to send its chip designs to Taiwan Semiconductor Manufacturing Co. (TSMC) for fabrication within the next few months, but the chip has not yet been formally announced.

The OpenAI chip’s full capabilities, technical details, and exact timeline are still unknown, but the company reportedly intends to iterate on the design and improve it over time, giving it leverage in negotiations with chip suppliers—and potentially granting the company future independence with a chip design it controls outright.

In the past, we’ve seen other tech companies, such as Microsoft, Amazon, Google, and Meta, create their own AI acceleration chips for reasons that range from cost reduction to relieving shortages of AI chips supplied by Nvidia, which enjoys a near-market monopoly on high-powered GPUs (such as the Blackwell series) for data center use.

In October 2023, we covered a report about OpenAI’s intention to create its own AI accelerator chips for similar reasons, so OpenAI’s custom chip project has been in the works for some time. In early 2024, OpenAI CEO Sam Altman also began spending considerable time traveling around the world trying to raise up to a reported $7 trillion to increase world chip fabrication capacity.

OpenAI’s secret weapon against Nvidia dependence takes shape Read More »

chatgpt-comes-to-500,000-new-users-in-openai’s-largest-ai-education-deal-yet

ChatGPT comes to 500,000 new users in OpenAI’s largest AI education deal yet

AI, AI assitants, AI in education, California State University, chatgpt, ChatGPT Edu, large language models, machine learning, openai, Ted Underwood / /

On Tuesday, OpenAI announced plans to introduce ChatGPT to California State University’s 460,000 students and 63,000 faculty members across 23 campuses, reports Reuters. The education-focused version of the AI assistant will aim to provide students with personalized tutoring and study guides, while faculty will be able to use it for administrative work.

“It is critical that the entire education ecosystem—institutions, systems, technologists, educators, and governments—work together to ensure that all students have access to AI and gain the skills to use it responsibly,” said Leah Belsky, VP and general manager of education at OpenAI, in a statement.

OpenAI began integrating ChatGPT into educational settings in 2023, despite early concerns from some schools about plagiarism and potential cheating, leading to early bans in some US school districts and universities. But over time, resistance to AI assistants softened in some educational institutions.

Prior to OpenAI’s launch of ChatGPT Edu in May 2024—a version purpose-built for academic use—several schools had already been using ChatGPT Enterprise, including the University of Pennsylvania’s Wharton School (employer of frequent AI commentator Ethan Mollick), the University of Texas at Austin, and the University of Oxford.

Currently, the new California State partnership represents OpenAI’s largest deployment yet in US higher education.

The higher education market has become competitive for AI model makers, as Reuters notes. Last November, Google’s DeepMind division partnered with a London university to provide AI education and mentorship to teenage students. And in January, Google invested $120 million in AI education programs and plans to introduce its Gemini model to students’ school accounts.

The pros and cons

In the past, we’ve written frequently about accuracy issues with AI chatbots, such as producing confabulations—plausible fictions—that might lead students astray. We’ve also covered the aforementioned concerns about cheating. Those issues remain, and relying on ChatGPT as a factual reference is still not the best idea because the service could introduce errors into academic work that might be difficult to detect.

ChatGPT comes to 500,000 new users in OpenAI’s largest AI education deal yet Read More »

hugging-face-clones-openai’s-deep-research-in-24-hours

Hugging Face clones OpenAI’s Deep Research in 24 hours

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On Tuesday, Hugging Face researchers released an open source AI research agent called “Open Deep Research,” created by an in-house team as a challenge 24 hours after the launch of OpenAI’s Deep Research feature, which can autonomously browse the web and create research reports. The project seeks to match Deep Research’s performance while making the technology freely available to developers.

“While powerful LLMs are now freely available in open-source, OpenAI didn’t disclose much about the agentic framework underlying Deep Research,” writes Hugging Face on its announcement page. “So we decided to embark on a 24-hour mission to reproduce their results and open-source the needed framework along the way!”

Similar to both OpenAI’s Deep Research and Google’s implementation of its own “Deep Research” using Gemini (first introduced in December—before OpenAI), Hugging Face’s solution adds an “agent” framework to an existing AI model to allow it to perform multi-step tasks, such as collecting information and building the report as it goes along that it presents to the user at the end.

The open source clone is already racking up comparable benchmark results. After only a day’s work, Hugging Face’s Open Deep Research has reached 55.15 percent accuracy on the General AI Assistants (GAIA) benchmark, which tests an AI model’s ability to gather and synthesize information from multiple sources. OpenAI’s Deep Research scored 67.36 percent accuracy on the same benchmark.

As Hugging Face points out in its post, GAIA includes complex multi-step questions such as this one:

Which of the fruits shown in the 2008 painting “Embroidery from Uzbekistan” were served as part of the October 1949 breakfast menu for the ocean liner that was later used as a floating prop for the film “The Last Voyage”? Give the items as a comma-separated list, ordering them in clockwise order based on their arrangement in the painting starting from the 12 o’clock position. Use the plural form of each fruit.

To correctly answer that type of question, the AI agent must seek out multiple disparate sources and assemble them into a coherent answer. Many of the questions in GAIA represent no easy task, even for a human, so they test agentic AI’s mettle quite well.

Hugging Face clones OpenAI’s Deep Research in 24 hours Read More »

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Microsoft now hosts AI model accused of copying OpenAI data

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Fresh on the heels of a controversy in which ChatGPT-maker OpenAI accused the Chinese company behind DeepSeek R1 of using its AI model outputs against its terms of service, OpenAI’s largest investor, Microsoft, announced on Wednesday that it will now host DeepSeek R1 on its Azure cloud service.

DeepSeek R1 has been the talk of the AI world for the past week because it is a freely available simulated reasoning model that reportedly matches OpenAI’s o1 in performance—while allegedly being trained for a fraction of the cost.

Azure allows software developers to rent computing muscle from machines hosted in Microsoft-owned data centers, as well as rent access to software that runs on them.

“R1 offers a powerful, cost-efficient model that allows more users to harness state-of-the-art AI capabilities with minimal infrastructure investment,” wrote Microsoft Corporate Vice President Asha Sharma in a news release.

DeepSeek R1 runs at a fraction of the cost of o1, at least through each company’s own services. Comparative prices for R1 and o1 were not immediately available on Azure, but DeepSeek lists R1’s API cost as $2.19 per million output tokens, while OpenAI’s o1 costs $60 per million output tokens. That’s a massive discount for a model that performs similarly to o1-pro in various tasks.

Promoting a controversial AI model

On its face, the decision to host R1 on Microsoft servers is not unusual: The company offers access to over 1,800 models on its Azure AI Foundry service with the hopes of allowing software developers to experiment with various AI models and integrate them into their products. In some ways, whatever model they choose, Microsoft still wins because it’s being hosted on the company’s cloud service.

Microsoft now hosts AI model accused of copying OpenAI data Read More »

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Anthropic builds RAG directly into Claude models with new Citations API

AI, AI Citations, AI confabulation, AI hallucination, Anthropic Claude, Citations, Claude, large language models, machine learning, openai / /

Willison notes that while citing sources helps verify accuracy, building a system that does it well “can be quite tricky,” but Citations appears to be a step in the right direction by building RAG capability directly into the model.

Apparently, that capability is not a new thing. Anthropic’s Alex Albert wrote on X, “Under the hood, Claude is trained to cite sources. With Citations, we are exposing this ability to devs. To use Citations, users can pass a new “citations: enabled:true” parameter on any document type they send through the API.”

Early adopter reports promising results

The company released Citations for Claude 3.5 Sonnet and Claude 3.5 Haiku models through both the Anthropic API and Google Cloud’s Vertex AI platform, but it’s apparently already getting some use in the field.

Anthropic says that Thomson Reuters, which uses Claude to power its CoCounsel legal AI reference platform, is looking forward to using Citations in a way that helps “minimize hallucination risk but also strengthens trust in AI-generated content.”

Additionally, financial technology company Endex told Anthropic that Citations reduced their source confabulations from 10 percent to zero while increasing references per response by 20 percent, according to CEO Tarun Amasa.

Despite these claims, relying on any LLM to accurately relay reference information is still a risk until the technology is more deeply studied and proven in the field.

Anthropic will charge users its standard token-based pricing, though quoted text in responses won’t count toward output token costs. Sourcing a 100-page document as a reference would cost approximately $0.30 with Claude 3.5 Sonnet or $0.08 with Claude 3.5 Haiku, according to Anthropic’s standard API pricing.

Anthropic builds RAG directly into Claude models with new Citations API Read More »

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OpenAI launches Operator, an AI agent that can operate your computer

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While it’s working, Operator shows a miniature browser window of its actions.

However, the technology behind Operator is still relatively new and far from perfect. The model reportedly performs best at repetitive web tasks like creating shopping lists or playlists. It struggles more with unfamiliar interfaces like tables and calendars, and does poorly with complex text editing (with a 40 percent success rate), according to OpenAI’s internal testing data.

OpenAI reported the system achieved an 87 percent success rate on the WebVoyager benchmark, which tests live sites like Amazon and Google Maps. On WebArena, which uses offline test sites for training autonomous agents, Operator’s success rate dropped to 58.1 percent. For computer operating system tasks, CUA set an apparent record of 38.1 percent success on the OSWorld benchmark, surpassing previous models but still falling short of human performance at 72.4 percent.

With this imperfect research preview, OpenAI hopes to gather user feedback and refine the system’s capabilities. The company acknowledges CUA won’t perform reliably in all scenarios but plans to improve its reliability across a wider range of tasks through user testing.

Safety and privacy concerns

For any AI model that can see how you operate your computer and even control some aspects of it, privacy and safety are very important. OpenAI says it built multiple safety controls into Operator, requiring user confirmation before completing sensitive actions like sending emails or making purchases. Operator also has limits on what it can browse, set by OpenAI. It cannot access certain website categories, including gambling and adult content.

Traditionally, AI models based on large language model-style Transformer technology like Operator have been relatively easy to fool with jailbreaks and prompt injections.

To catch attempts at subverting Operator, which might hypothetically be embedded in websites that the AI model browses, OpenAI says it has implemented real-time moderation and detection systems. OpenAI reports the system recognized all but one case of prompt injection attempts during an early internal red-teaming session.

OpenAI launches Operator, an AI agent that can operate your computer Read More »