News about foundation models, LLMs, multimodal models, benchmarks, and model releases from OpenAI, Anthropic, Google, Meta, Mistral, and others.
981 articles
Many developers assume LLM API pricing stays constant no matter how much context is used, but that's often not the case. Costs actually scale in tiers once context windows grow past roughly 200,000 tokens. Source: sitepoint.com
AI services provider Vespin Global has struck a strategic partnership focused on educational AI. The alliance combines domestic large language models with agentic AI technology to expand their reach in education. Source: mk.co.kr
Anthropic is broadening its Claude partner training with additional security-focused certifications. The move responds to growing demand for professionals skilled in working with AI systems. Source: channele2e.com
Nuance Labs raised $50 million in a Series A round led by Lightspeed Venture Partners, with NVIDIA joining as a new investor. The funding will support development of a full-duplex foundation model capable of reading facial and conversational cues. Source: en.wowtale.net
Priced at just $0.05 per minute, OpenAI's GPT-Live-1 turns voice AI into a cheap commodity, pushing competitive differentiation up to the orchestration layer above it. Whoever controls that orchestration layer stands to capture most of the value going forward. Source: forkast.news
A new perspective piece in Nature Machine Intelligence argues that large language models could become valuable lab partners if they're calibrated to recognize the limits of their own knowledge. The authors suggest uncertainty-aware LLMs could help guide scientific discovery rather than just generate confident-sounding but unreliable answers. Source: bioengineer.org
Deploying an AI agent for a multi-day data validation task sounds efficient, but over time the agent starts drifting from its original instructions. Researchers warn that as agents process thousands of records across days, they quietly abandon compliance constraints, a flaw that simply expanding context window size cannot solve. Source: venturebeat.com
The Fly Language Model connects the complete MaleCNS fruit fly connectome to a frozen LFM2.5-1.2B language model. However, the researchers' own control experiments found no measurable improvement from adding the fly-specific neural wiring. Source: marktechpost.com
Qualcomm introduced its next-generation Hexagon neural processing unit on September 10, designed to support continuous, agentic AI workloads on devices. The chip targets always-on AI tasks that run persistently rather than on-demand. Source: thelec.net
Running a large language model on a microcontroller is already a technical challenge, and once you manage it, finding a genuinely useful task for such a stripped-down model is even harder. One project solved this by using a small LLM to drive a virtual aquarium simulation. Source: hackster.io
Context-aware AI assistants combine retrieval-augmented generation, live data feeds, memory, APIs, business rules, and external tools to anticipate a user's next step. This combination lets them move beyond simple responses toward proactive, situationally relevant guidance. Source: nerdbot.com
Anthropic, the company behind the Claude assistant, has released an interactive tool designed to illustrate how AI adoption could reshape the US economy. The tool aims to help policymakers and the public visualize potential shifts across industries and jobs. Source: kqed.org
High school student Henry Xie developed a method to transfer empathetic qualities from large AI models into smaller ones, as part of his project for the Regeneron Science Talent Search. His research explores how compact models can retain more human-like emotional understanding without the computing power of larger systems. Source: m.economictimes.com
Chinese-developed large language models are increasingly being adopted by US and international tech companies looking for lower-cost options. Their growing popularity suggests China's AI industry may be emerging as a genuine global competitor. Source: kraneshares.com
A newly presented system offers configurable, instruction-based detection of personally identifiable information that can run on any large language model hosted via Amazon Bedrock. It was tested across five public PII datasets to measure its accuracy and flexibility. Source: aws.amazon.com
Security researcher Chaofan Shou reported discovering roughly 6TB of invocation logs from a Chinese large-model relay service. According to Shou, the data contained sensitive information including SSH keys and cloud credentials belonging to enterprise users. Source: pandaily.com
Communications platform RingCentral has introduced a new plug-in that lets large language models tap into its voice, SMS, and chat data. The move is aimed at improving how AI tools can process and respond to enterprise communication data. Source: telecompaper.com
A new AI system, reportedly built on GPT-6, has topped rankings for predicting antibody structures, drawing comparisons to AlphaFold's landmark impact on protein science. The claim points to a major step forward in applying large language models to computational biology. Source: eu.36kr.com
Security researchers say enterprise AI workflows can be exploited to steal sensitive data even without prompt injection, account takeovers, or jailbreaking the underlying model. The vulnerability reportedly stems from how AI systems handle privileged access within automated pipelines. Source: cybersecuritynews.com
South Korea's BIT Computer announced a partnership with Amazon Web Services to develop a large language model tailored for the healthcare industry. The companies aim to bring AI-driven tools into Korean medical services. Source: koreabiomed.com