AGI

Stanford researchers used generative AI (Evo 2) to design and synthesize novel bacteriophages. The AI generated nearly 300 potential phage genomes, with 16 showing potent activity against E. coli. This approach, utilizing computational screening and a cocktail strategy, enhances therapeutic potential and offers a new weapon against antibiotic resistance. The Evo 2 model is now open-source to accelerate synthetic biology innovation.

Instagram’s AI curates content, but genuinely human content is increasingly prioritized. AI handles intricate engagement mechanics and automation, freeing creators for strategy and storytelling. While AI chatbots streamline communication and production, authentic human interaction and ingenuity remain paramount. The platform aims to balance AI-driven efficiency with the preservation of human creativity and connection.

Alibaba is reportedly moving towards a revenue-sharing model for its Qwen open-weight AI. Commercial users leveraging the model for revenue generation will need commercial agreements. This marks a shift from traditional licensing, influenced by trends seen with models like Moonshot’s Kimi K3, which also employs revenue-sharing for large-scale commercial applications. The strategy aims to monetize advanced AI technologies beyond basic licensing, acknowledging the significant infrastructure costs associated with deploying large models.

Research shows user expertise critically impacts AI explainability in healthcare. Non-experts, particularly with LLM explanations, tend to defer to AI, increasing errors. Primary care physicians perform best with AI predictions alone, being more critical of explanations. The study stresses tailoring AI interfaces to user expertise to avoid automation bias and ensure safe integration.

Paige and Microsoft’s PRISM2 is a revolutionary AI for digital pathology. It interprets whole-slide images and generates natural language answers to diagnostic questions, moving beyond simple pixel identification. Trained on 2.3 million whole-slide images and clinical dialogue from 685,507 pathology reports, PRISM2 consolidates tile embeddings into a single representation. GPT-4o was used to create question-and-answer pairs from this data, ensuring authentic clinical reasoning for intuitive diagnostic insights.

Alibaba launches Qwen3.8-Max, a 2.4 trillion parameter AI model, employing a mixture-of-experts design for efficiency. This move intensifies competition with rivals like DeepSeek, which challenges with aggressive, low-cost pricing for its V4-Flash model. While Qwen3.8-Max boasts multimodal capabilities and a large context window, DeepSeek prioritizes affordability, making cost-per-task a key battleground in the AI market. Both companies also offer open-weight versions, increasing accessibility for developers.

Red Hat launches “asago,” an open-source initiative to automate AI governance from policy to production code. Asago maps policies to risks, assesses them with tailored scenarios, recommends mitigations, and orchestrates deployment, significantly reducing manual effort. It ensures continuous audit trails and infrastructure-agnostic configurations. The project, a collaborative effort with major tech and academic institutions, aims to address the growing need for AI safety and compliance in a scalable manner.

Article 50 of the EU AI Act mandates transparency for generative AI. Providers and deployers must disclose when users interact with AI or when content is AI-generated, particularly for deepfakes and public interest texts. This aims to prevent manipulation and deception. Specific requirements include machine-readable markings for synthetic media and clear notifications for emotion recognition/biometric categorization tools. Enforcement involves national authorities, the AI Office, and the EDPS. A voluntary Code of Practice aids compliance with marking obligations.

GSK is expanding its AI-driven drug discovery efforts through a significant collaboration with Relation Therapeutics. This partnership leverages Relation’s expertise in generating high-volume, sophisticated human cell datasets. These datasets will train advanced AI models, including Relation’s MORGAN platform, to rapidly pinpoint novel drug targets. Building on prior successful collaborations, this agreement integrates cutting-edge data generation with AI model development for more precise therapeutic discovery.

OpenAI is proactively aligning its safety, security, and transparency initiatives with the EU AI Act’s GPAI Code of Practice. The company highlights its rigorous testing, system cards, red-teaming, and internal governance frameworks as evidence of its commitment. OpenAI also addresses AI-generated content provenance through Content Credentials and SynthID watermarking, and manages dual-use risks in cybersecurity via its EU Cyber Action Plan. The company emphasizes the need for flexible regulations to keep pace with evolving AI technology.