Machine Learning

Explore articles tagged with Machine Learning

#AI#Google AI#Google

Google’s Gemini can now run on a single air-gapped server — and vanish when you pull the plug

Cirrascale Cloud Services today announced it has expanded its partnership with Google Cloud to deliver the Gemini model on-premises through Google Distributed Cloud, making it the first neocloud provider to offer Google's most advanced AI model as a fully private, disconnected appliance. The announcement, timed to coincide with Google Cloud Next 2026 in Las Vegas, addresses a stubborn problem that has plagued regulated industries since the generative AI boom began: how to access frontier-class A.

#AI#Anthropic#Claude

Anthropic walks into the White House and Mythos is the reason Washington let it in

When we covered Project Glasswing earlier this month, the story was about a model too dangerous to release publicly and what Anthropic decided to do with it instead. On Friday, Anthropic CEO Dario Amodei walked into the West Wing for a meeting with White House Chief of Staff Susie Wiles.

#AI#Large Language Models#NLP

Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use inference-time scaling techniques to increase the accuracy of model responses, such as drawing multiple reasoning samples from a model at deployment.

#AI#Anthropic#Claude

Anthropic just launched Claude Design, an AI tool that turns prompts into prototypes and challenges Figma

Anthropic today launched Claude Design, a new product from its Anthropic Labs division that allows users to create polished visual work — designs, interactive prototypes, slide decks, one-pagers, and marketing collateral — through conversational prompts and fine-grained editing controls. The release, available immediately in research preview to all paid Claude subscribers, is the company's most aggressive expansion beyond its core language model business and into the application layer that has h.

#AI#Artificial Intelligence#AI Models

Why The US-China AI gap closed. The responsible AI gap didn’t

The assumption that the US holds a durable lead in AI model performance is not well-supported by the data, and that is just one of the uncomfortable findings in Stanford University’s 2026 AI Index Report, published this week. The report, produced by Stanford’s Institute for Human-Centred Artificial Intelligence, is a 423-page annual assessment of where […] The post The US-China AI gap closed.

#AI#Anthropic#Claude

Anthropic’s Claude Managed Agents gives enterprises a new one-stop shop but raises vendor 'lock-in' risk

Anthropic announced a new platform last week, Claude Managed Agents, aiming to cut out the more complex parts of AI agent deployment for enterprises and competes with existing orchestration frameworks. Claude Managed Agents is also an architectural shift: enterprises, already burdened with orchestrating an increasing number of agents, can now choose to embed the orchestration logic in the AI model layer.

#AI#Anthropic#Claude

Is Anthropic 'nerfing' Claude? Users increasingly report performance degradation as leaders push back

A growing number of developers and AI power users are taking to social media to accuse Anthropic of degrading the performance of Claude Opus 4.6 and Claude Code — intentionally or as an outcome of compute limits — arguing that the company’s flagship coding model feels less capable, less reliable and more wasteful with tokens than it did just weeks ago.

#AI#Machine Learning#AI Models

Five signs data drift is already undermining your security models

Data drift happens when the statistical properties of a machine learning (ML) model's input data change over time, eventually rendering its predictions less accurate. Cybersecurity professionals who rely on ML for tasks like malware detection and network threat analysis find that undetected data drift can create vulnerabilities.

#AI#AI Models#Machine Learning

Your developers are already running AI locally: Why on-device inference is the CISO’s new blind spot

For the last 18 months, the CISO playbook for generative AI has been relatively simple: Control the browser. Security teams tightened cloud access security broker (CASB) policies, blocked or monitored traffic to well-known AI endpoints, and routed usage through sanctioned gateways.

#AI#AI Models#Machine Learning

The Download: an exclusive Jeff VanderMeer story and AI models too scary to release

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. Constellations —Constellations is a short story by Jeff VanderMeer, the author of the critically acclaimed, bestselling Southern Reach series.

#AI#Meta#Technology

Meta has a competitive AI model but loses its open-source identity

The open-source AI movement has never lacked for options. Mistral, Falcon, and a growing field of open-weight models have been available to developers for years.

#AI#Anthropic#Claude

Anthropic keeps new AI model private after it finds thousands of external vulnerabilities

Anthropic’s most capable AI model has already found thousands of AI cybersecurity vulnerabilities across every major operating system and web browser. The company’s response was not to release it, but to quietly hand it to the organisations responsible for keeping the internet running.

#AI#AI Models#Machine Learning

As models converge, the enterprise edge in AI shifts to governed data and the platforms that control it

Presented by Box As frontier models converge, the advantage in enterprise AI is moving away from the model and toward the data it can safely access. For most enterprises, that advantage lives in unstructured data: the contracts, case files, product specifications, and internal knowledge.

#AI#Anthropic#Claude

The one piece of data that could actually shed light on your job and AI

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

#AI#AI Models#Machine Learning

As AI agents take on more tasks, governance becomes a priority

AI systems are starting to move beyond simple responses. In many organisations, AI agents are now being tested to plan tasks, make decisions, and carry out actions with limited human input.

#AI#AI Models#Machine Learning

OCSF explained: The shared data language security teams have been missing

The security industry has spent the last year talking about models, copilots, and agents, but a quieter shift is happening one layer below all of that: Vendors are lining up around a shared way to describe security data. The Open Cybersecurity Schema Framework (OCSF), is emerging as one of the strongest candidates for that job.

#AI#Anthropic#Claude

Anthropic cuts off the ability to use Claude subscriptions with OpenClaw and third-party AI agents

Are you a subscriber to Anthropic's Claude Pro ($20 monthly) or Max ($100-$200 monthly) plans and use its Claude AI models and products to power third-party AI agents like OpenClaw? If so, you're in for an unpleasant surprise. Anthropic announced a few hours ago that starting tomorrow, Saturday, April 4, 2026, at 12 pm PT/3 pm ET, it will no longer be possible for those Claude subscribers to use their subscriptions to hook Anthropic's Claude models up to third-party agentic tools, citing the st.

#AI#Autonomous Systems#Robotics

Breaking: KiloClaw targets shadow AI with autonomous agent governance

With the launch of KiloClaw, enterprises now have a tool to enforce governance over autonomous agents and manage shadow AI. While businesses spent the last year securing large language models and formalising vendor agreements, developers and knowledge workers started moving on their own.

#AI#Anthropic#Claude

In the wake of Claude Code's source code leak, 5 actions enterprise security leaders should take now

Every enterprise running AI coding agents has just lost a layer of defense. On March 31, Anthropic accidentally shipped a 59.

#AI#Large Language Models#NLP

Shifting to AI model customization is an architectural imperative

In the early days of large language models (LLMs), we grew accustomed to massive 10x jumps in reasoning and coding capability with every new model iteration. Today, those jumps have flattened into incremental gains.