According to FoxNewsAI, rapid AI layoffs risk lower productivity, rising rehiring costs, and delayed model deployments, per Fox News analysis of market data.

According to SawyerMerritt, Grok reaches 117M MAUs as X’s integrated AI platforms report 1.3B supported accounts and 550M MAUs, signaling rapid scale.

According to emollick, OpenAI’s o1 graph shows no ability decay with more compute, hinting broad general LLM gains, per polynoamial’s launch comments.

According to AndrewYNg, DeepLearning.AI launched a course on self-evaluating agents for image and video, combining similarity, LLM judges, and rubrics.

According to @emollick, Google hid Gemini thinking traces behind a menu with minimal summaries, limiting trust for serious work, per his tweet.

According to sundarpichai, Gemini 3.5 Flash shows strong evals as a workhorse model, signaling efficient multimodal performance for real-world apps.

According to @emollick, Gemini 3.5 Flash is very fast and capable, powering a procedural one-shot towns gallery and self-correcting an initial error.

According to @GeminiApp, Google IO 2026 is live, signaling new Gemini upgrades and AI features for developers and businesses.

According to @GeminiApp, Google IO Day One will unveil new Gemini updates via livestream at 10am PT.

According to DeepLearningAI, a new guide teaches spec-driven development with coding agents to boost reliability and speed for software teams.

According to emollick, SF startups now hire “wizards” for execs’ strategy, signaling new AI ops roles and culture shifts, as reported by deepfates posts.

According to @ylecun, Jacob Effron’s interview covers LLM limits, robotics paths, AMI world models, Meta exit, and 2027 predictions.

According to PixVerse... Panel covered Qwen and Ant LingGuang LLM strategies and OpenClaw perspectives at MU Shanghai, highlighting business use cases.

According to @godofprompt, routing cheap models for simple tasks and stronger models for critical ones cuts costs and adds fallback resilience.

According to TheRundownAI, GPT-4 level models can draft publishable database chapters, signaling major shifts for textbook production economics.

According to @_avichawla, a free roadmap covers prompt engineering, RAG, fine-tuning, agents, deployment, optimization, and safety with open-source links.

According to @sama, enabling developers to evolve into superheroes beats replacement, noting one skilled engineer now achieves outsized impact.

According to @godofprompt, a Domain Vocabulary prompt helps teams name parts of AI systems to cut ambiguity and ship faster.

According to Ethan Mollick on X, assigning expert personas like physicist or lawyer barely changes LLM answer accuracy, based on controlled tests.

According to @emollick, ChatGPT, Claude, and Gemini often cite four poems about making LLMs, signaling shared cultural priors in AI outputs.