AI Models

Explore articles tagged with AI Models

#AI#Anthropic#Claude

Alibaba's proprietary Qwen3.7-Max can run for 35 hours autonomously and supports external harnesses like Anthropic's Claude Code

The AI industry has fully entered the "agent era," a paradigm where AI models do far more than generate text — they now actively plan, execute, and course-correct complex tasks over days rather than seconds. Thus, it's perhaps unsurprising to see Chinese e-commerce giant Alibaba's famed Qwen Team of AI researchers release a model capable of performing autonomous agentic AI work over multiple days: that model has arrived in the form of Qwen3.

#Google AI#Google#Technology

Google's Managed Agents API promises one-call deployment at the cost of execution layer control

At Google I/O, the company unveiled Managed Agents in its Gemini API — a service that promises to collapse weeks of agent deployment work into a single API call. It's also a sign that Google believes its ecosystem, including the newly launched Antigravity CLI, is ready to own the execution layer end-to-end.

#AI#Artificial Intelligence#Google AI

Google says Gemini 3.5 Flash can slash enterprise AI costs by more than $1 billion a year

Google unveiled Gemini 3.5 Flash at its annual I/O developer conference on Tuesday, a new artificial intelligence model that the company says shatters what had become a seemingly iron law of the AI industry: that the smartest models must also be the slowest and most expensive to run.

#AI#Large Language Models#NLP

Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via cosine similarity — is effective for unstructured semantic search.

#AI#Autonomous Systems#Robotics

The enterprise risk nobody is modeling: AI is replacing the very experts it needs to learn from

For AI systems to keep improving in knowledge work, they need either a reliable mechanism for autonomous self-improvement or human evaluators capable of catching errors and generating high-quality feedback. The industry has invested enormously in the first.

#AI#Autonomous Systems#Robotics

Establishing AI and data sovereignty in the age of autonomous systems

When generative AI first moved from research labs into real-world business applications, enterprises made a tacit bargain: “Capability now, control later.” Feed your proprietary data into third-party AI models, and you will get powerful results.

#AI#Artificial Intelligence#Meta

AI IQ is here: a new site scores frontier AI models on the human IQ scale. The results are already dividing tech.

For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is applying the same metaphor to artificial intelligence, assigning estimated intelligence quotients to more than 50 of the world's most powerful language models and plotting them on a standard bell curve.

#AI#OpenAI#ChatGPT

Hugging Face hosted malicious software masquerading as OpenAI release

A malicious Hugging Face repository that posed as an OpenAI release delivered infostealer malware to Windows machines and recorded about 244,000 downloads before removal, according to research from AI security firm HiddenLayer. The number of downloads may have been artificially inflated by the attackers to make the model seem more popular, so the extent of […] The post Hugging Face hosted malicious software masquerading as OpenAI release appeared first on AI News.

#AI#AI Models#Machine Learning

Thinking Machines shows off preview of near-realtime AI voice and video conversation with new 'interaction models'

Is AI leaving the era of "turn-based" chat? Right now, all of us who use AI models regularly for work or in our personal lives know that the basic interaction mode across text, imagery, audio, and video remains the same: the human user provides an input, waits anywhere between milliseconds to minutes (or in some cases, for particularly tough queries, hours and days), and the AI model provides an output. But if AI is to really take on the load of jobs requiring natural interaction, it will need t.

#AI#Large Language Models#NLP

GPT-5.5 Instant shows you what it remembered — just not all of it

OpenAI updated the default model for ChatGPT to its new GPT-5.5 Instant, along with a new memory capability that finally shows which context shaped responses — at least some of them.

#AI#Large Language Models#NLP

xAI launches Grok 4.3 at an aggressively low price and a new, fast, powerful voice cloning suite

While Elon Musk faces off against his former colleague and OpenAI co-founder Sam Altman in court, Musk's rival firm xAI, founded to take on OpenAI, isn't slowing down on launching competitive new products and services. Last night, xAI shipped a new, proprietary base large language model (LLM), Grok 4.

#AI#Large Language Models#NLP

This startup’s new mechanistic interpretability tool lets you debug LLMs

The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a model’s behavior—during training. This could give model makers more fine-grained control over how this technology is built than was once thought possible.

#AI#OpenAI#ChatGPT

Claude Code, Copilot and Codex all got hacked. Every attacker went for the credential, not the model.

On March 30, BeyondTrust proved that a crafted GitHub branch name could steal Codex’s OAuth token in cleartext. OpenAI classified it Critical P1.

#AI#OpenAI#ChatGPT

Amazon’s OpenAI gambit signals a new phase in the cloud wars — one where exclusivity no longer applies

Amazon Web Services on Tuesday launched one of the most consequential enterprise AI plays in the company's 20-year history, simultaneously bringing OpenAI's most powerful models to its Bedrock platform, unveiling a new agentic developer framework, releasing a desktop AI productivity tool called Amazon Quick, and expanding its Amazon Connect service from a single contact-center product into a family of four agentic AI solutions targeting supply chains, hiring, healthcare, and customer experience.

#AI#Machine Learning#AI Models

New IDC: How EMEA CIOs can jumpstart AI rollouts

Getting stalled enterprise AI rollouts in the EMEA region moving again will require CIOs to aggressively audit their systems. Over the past 18 months, AI deployments across Europe advanced far beyond initial testing.

#AI#ChatGPT#OpenAI

GPT-5.5 is OpenAI’s most capable agentic AI model yet–at twice the API price

OpenAI launched GPT-5.5 on April 23 as what it calls “a new class of intelligence for real work and powering agents,” and the framing is deliberate.

#AI#AI Models#Machine Learning

Context decay, orchestration drift, and the rise of silent failures in AI systems

The most expensive AI failure I have seen in enterprise deployments did not produce an error. No dashboard turned red.

#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.