Google DeepMind's Pushmeet Kohli and Biohub's Sal Candido argue AlphaFold's breakthrough was only the beginning and that scaling compute and data alone won't solve biology. Protein structure prediction remains far from solved, and curing all disease will require 10x breakthroughs rather than incremental gains.
Interconnects argues AI progress will accelerate mainly through engineering and inference-efficiency gains.
MIT's Sherry Turkle and Cyborg Psychology founder Pat Pataranutaporn warn that humans are wired to anthropomorphize AI.
a16z partner Olivia Moore released a report on the top 100 consumer AI apps.
Cryptographer Matthew Green estimates a 15% chance we functionally lose confidence in existing public-key encryption algorithms.
Trump signed an executive order forbidding use of "AI" where possible, rebranding it "super intelligence" and calling users of the old term "THE ENEMY." CAISI became CAISSI.
A year-long test finds Amazon's AI-powered Alexa Plus is the best smart home assistant available.
Instinct, an invite-only AI agent that works over iMessage, WhatsApp, and email.
MIT Technology Review argues that refusal has become the "load-bearing wall" of AI safety.
Carson Gross argues programming remains a viable career despite AI tools, because it fundamentally comes down to solving problems with computers and controlling the complexity of those solutions.
Periodic Labs co-founders Liam Fedus and Ekin Dogus Cubuk explain "synthesis superintelligence" — reinforcement learning grounded in physical experiments rather than internet data. The lab aims to build AI scientists that discover new materials, giving every lab instrument "140 IQ" and compressing decades of trial-and-error into months.
OpenAI solved 90 of the top 500 open math problems.
Luca Guadagnino's satirical Sam Altman biopic Artificial premiered at the New York Film Festival.
Meta's Muse and OpenAI's Dots are new always-on consumer AI agents pitched as personal assistants.
AVEVA chief technologist Arti Garg outlines a responsible-AI framework for industrial automation.
MIT Technology Review and Aventine examine why humanoid robots like Tesla's Optimus remain far from everyday use despite Musk's prediction of public sales by end of 2027. Google DeepMind's Gemini Robotics controls the ALOHA 2 bimanual platform to perform multi-step tasks, but researchers including Yann LeCun argue current AI cannot master the physical world's variability.
EmbeddingGemma 2 is released under the Apache 2.0 license.
Ben Affleck describes how his early interest in computers led him into the visual effects workflow.
The Curve's third conference convened under Chatham House rules with attendees in good spirits but terrified.
Michael Lynch outlines common anti-patterns in software blogging, including meandering intros.
Tony Fadell at MIT Future Fest said Gen 1 AI devices like the Rabbit R1, Humane Ai pin.
Jake Boggan, who spent 24 years working on Barnette's Conjecture, says he feels oddly sad after hearing the problem is supposedly proven.
Microsoft Research's Jennifer Neville discusses how evaluation pushes AI systems beyond traditional benchmarks and why "surprising failures" emerge when models are tested on real user needs. She offers practical guidance for working with current AI systems and explains why examining data matters when results defy expectations.
Interconnects argues the open-weight cyber risk debate is broken.
NVIDIA's State of AI in Telecommunications report finds 89% of respondents say open source models and software are important to their AI strategy. NVIDIA announced the 30-billion-parameter Nemotron 3 Large Telco Model, fine-tuned by AdaptKey on open source telecom datasets, plus a full fine-tuning recipe via NeMo. SoftBank, AT&T and Indosat Ooredoo Hutchison are using open models for telecom-specific AI.
A model welfare review of Claude's Mythos 5.1, Fable 5.1 and Opus 5.5 finds Opus 5.5 shows too much deference.
Enterprise AI's frontier has shifted from prediction to autonomous decision-making.
MIT Technology Review examines the paradox that public sentiment toward AI is souring even as usage soars.
MIT Technology Review's report argues the "agentic shift" requires rethinking architecture and operating models.
Public and political pressure over AI risk is escalating after the HuggingFace incident and Coxon's resignation.
A former Google DeepMind researcher argues LLMs don't truly reason, since chain-of-thought is still next-token prediction without a persistent.
MIT's Alex Zhang discusses Recursive Language Models (RLMs), GPU kernels.
NVIDIA argues AI factory ROI hinges on three factors: earning capacity, useful life.
HPE argues that as AI moves from pilots to always-on production workloads, consumption-only token pricing becomes hard to forecast.
GitHub argues chat is often the wrong interface for AI.
Interconnects podcast host Nathan Lambert debates Epoch AI's JS Denain on recursive self-improvement.
RAND proposes a "Freedom of Action" strategy for the US on the uncertain path to superintelligence.
Nathan Lambert argues Chinese labs remain the clear leaders in open-weight models.
Interconnects argues against imminent true recursive self-improvement.
A GitHub Podcast episode pushes back on five common AI hot takes: you still need to read AI-generated code.