Lilith · selected stories
What is actually happening in AI. Selected stories, context and opinion without the promotional noise.
Atom feed ↗A new Google Workspace and Gemini commercial, showing the “founding fathers” creating the Declaration of Independence via shared docs, sparked severe criticism for rewriting history and marketing tone-deafness.
Google has sued the alleged China-based Outsider Enterprise network, saying it used Gemini to help build phishing sites. Google links the operation to 9,000 fake websites, 1 million fraudulent URLs and 2.5 million text messages in two weeks.
Google Research introduced TabFM, a zero-shot foundation model for classification and regression on tables. The product hook is BigQuery ML: some work around feature engineering, tuning and training may move into a SQL call.
404 Media highlighted the recurring figure of Elias Thorne in chatbot stories, and the related research puts numbers on it: 20,000 generated stories repeatedly return to lighthouses, keepers and a small set of names. The issue is mode collapse in creative output, not a lack of vocabulary.
Google Research examines why chain-of-thought helps LLMs answer simple factual questions. The study on Gemini 2.5 and Qwen3-32B points to two mechanisms: extra computation in generated tokens and factual priming.
Google has rolled out frozen Multi-Token Prediction for Gemini Nano v3 on Pixel 9 and Pixel 10 phones. The practical point is simple: faster local AI without replacing the base model or adding a separate drafter into memory.
Google introduced Gemma 4 12B as a unified, encoder-free multimodal model designed for high performance directly on a laptop. The practical question is whether a 12B model can deliver enough quality for local or edge use without heavy cloud infrastructure.
Google announced Gemini 3.5 Live Translate for near real-time voice-to-voice translation across more than 70 languages. The practical question is not just translation quality, but latency, voice stability, Meet availability and who carries the risk when a live call is mistranslated.
Google released Android 17 and Wear OS 7 first for Pixel devices, alongside a Pixel Drop with Gemini Omni, Lyria 3 and translation features for the Pixel 10a. The bigger signal is not the OS update itself, but Google using Android as a distribution layer for AI models on the device.
Sensor Tower says ChatGPT's share of the AI assistant market fell to 46.4 % by the end of May, even as it still has more than 1.1 billion monthly users. The bigger story is market fragmentation, where Google's distribution and Claude's paid conversion are starting to matter.
Google introduced an agentic RAG system for Gemini Enterprise Agent Platform that checks whether it has enough context before answering. For companies, that brake matters more than another polished retrieval layer.
Google is launching Gemini 3.5 Live Translate for near real-time speech-to-speech translation across more than 70 languages. Users will see convenience first, but companies will care about latency, audit and trust in a voice speaking for someone else.
Google Research presents a private analytics approach combining secure aggregation with TEEs for safer measurement of on-device AI.
Last Week in AI #341 connects Musk losing against OpenAI, Gemini updates from IO 2026 and other AI market signals.
AI Snake Oil examines the claim that Google AI agents built an operating system for $916. The key point: agentic announcements need a different type of verification than chat benchmarks, because a big goal and a few steps in a demo environment are easy to inflate.
LWiAI Podcast episode 246 from 26 May 2026 is a map, not a single thesis. Google I/O, coding agents, legal pressure around OpenAI and safety research landed in the same week and sketch four simultaneous pressures on the AI market.
At I/O 2026, Google Research showed Gemini for Science, ERA and Co-Scientist as systems where AI takes over research middle steps: literature review, writing code, iterating hypotheses. Risks of false certainty and vendor lock-in are substantial.
DeepMind introduced AlphaEvolve as a Gemini-powered evolutionary loop that automatically discovers better algorithms. Concrete production results: 30 % fewer errors in genomics, 20 % lower write amplification for Spanner, Klarna doubled transformer training speed.
Google DeepMind released Gemini 2.5 Computer Use in preview: a specialized model for agents that drive user interfaces. Unlike general-purpose Gemini 2.5 Pro, this model was trained specifically for screen interaction, not just reasoning about it.
