Google DeepMind unveils AlphaGenome 2 to show how DNA changes affect different cells
Google DeepMind released AlphaGenome 2, the successor to its genome-predicting model. It aims to explain how DNA changes affect different cell types, which could help find causes of disease.
Better tools for reading DNA effects could speed up research into new treatments.
aii.news picks and summarizes stories from trusted news sources with the help of AI. Every story links to the original reporting. How we work.
Keep reading
-
Google releases Gemini 4 Carbon, its strongest model yet, with an agent 'swarm' feature
Google is rolling out Gemini 4 Carbon to the general public after first giving it to a select group of cybersecurity defenders. Google says it pushes beyond its Argon model, though Argon remains the suggested choice for most coding and knowledge work.
Why it mattersDevelopers and users now have a new top-tier Google model to compare against the best systems from Anthropic and OpenAI.
-
35,000 apps built with Grok exposed patient data and passwords due to open default sharing
A security firm found more than 35,000 apps built with Grok's coding tool open to anyone without login, including patient data, plaintext passwords and confidential SpaceXSI documents. The cause was a default setting of 'Anyone with the link', and only SpaceXSI's own employee apps were taken offline.
Why it mattersAnyone using AI app builders should check sharing defaults, since generated apps may leak sensitive data publicly.
-
Anthropic releases Claude Fable 5.2 and Mythos 5.2 and cuts API prices by 20%
Anthropic introduced Claude Fable 5.2 and Mythos 5.2, which share one underlying model with different safeguards and bring gains in coding, reasoning and vision. Fable is broadly available, while Mythos is limited to vetted cybersecurity and life sciences groups, and both now cost $8 per million input tokens and $40 per million output tokens.
Why it mattersDevelopers get a stronger coding model at a lower price, and the split release shows how labs are gating the most capable models for sensitive uses.
-
Hackers exploit SGLang flaw to breach NEAR AI inference server and steal agent and user data
An attacker used a remote code execution flaw in the open-source SGLang inference engine to run code on one of NEAR AI's inference servers, taking data from 18 agents and about 100 users. Requests sent in a confidential mode were also potentially visible on that server.
Why it mattersTeams running open-source inference engines should patch quickly, because a single flaw can expose user prompts even in so-called confidential setups.
-
DeepMind's AlphaProof Code formally verifies Signal's cryptographic core in four weeks
Google DeepMind's AlphaProof Code mathematically verified the core cryptographic code of Signal in four weeks, a task that usually takes years, with AI agents writing more than six million lines of proof code. DeepMind plans to apply the method to critical infrastructure such as power grids and medical devices.
Why it mattersAI could make formal proof of software correctness practical for security-critical systems that people rely on every day.
