#Google

Show HN: ShadowDiff – Shadow testing and SQL diffing for AI-migrated back ends

ShadowDiff is a network proxy and analysis engine that mirrors live HTTP traffic to both a legacy service and its AI-refactored candidate, then runs a 3-way diff with noise cancellation plus SQL side-effect comparison to isolate genuine regressions. It integrates with Envoy/Istio request mirroring, uses Google Gemini (gemini-2.0-flash) to synthesize regression tests, can open GitHub PRs with fixes, and offers a `shadowdiff gate` CLI for CI/CD quality gating. The project is MIT-licensed and includes Docker Compose and Kubernetes/Istio deployment examples.

Bing is the anti-AI search engine you should be using

PCWorld argues that Bing is a better choice than AI-heavy search engines because it surfaces human-authored content and links to original sources, while keeping Microsoft Copilot as an optional button rather than forcing AI summaries to the top of results. The article says AI search engines like Google's AI Mode can hide sources and produce misleading information, citing a ChatGPT example, and notes that Google's AI results can be partly avoided with tricks like adding "-ai" or "udm=14" to a query or switching Chrome's default search engine to Bing.

The AI graveyard: a running list of projects and startups that didn’t make it

This roundup catalogs AI products, startups, and corporate initiatives that shut down, pivoted, or missed expectations, including Character.ai's bankruptcy filing, Ollie's shutdown, OpenAI's discontinued Atlas browser and Sora, and hardware failures like the Humane AI Pin. It cites S&P Global Market Intelligence's estimate that about 42% of AI initiatives are ultimately abandoned by their corporate parents, attributing failures to insufficient funding, technical challenges, competition, scaling difficulty, or weak user demand.

Gemini 4 Carbon takes the MathArena crown but costs 15 times more than GPT-6.1 Sol

Google's Gemini 4 Carbon became the first non-OpenAI model in a while to top the MathArena math benchmark, displacing GPT-6.1 Sol, with Claude Fable 5.2 taking second place. Its most common failure mode is exceeding the time limit, and in one case it ran a script for more than eleven hours without checking its progress. With the reasoning settings used in testing, Carbon and Fable 5.2 cost roughly 15 and 40 times as much as GPT-6.1 Sol, respectively.

The Missing Ring-0 Protections for AI Agents

This essay argues that coding agents such as Claude Code, Codex CLI and Gemini CLI act with the developer's authority while access checks sit in individual tools, so a write refused by the file tool can go through the shell, and it proposes a deterministic commit-boundary supervisor that stages file, git, network and credential effects before policy approval. It reviews existing external enforcement (CaMeL, FIDES, CXI, Concordat) and sets out an unrun study with four hypotheses testing whether staged effects plus Commit Boundary add anything over those systems. Nothing described has been built, and the author states Commit Boundary is an unvalidated conceptual architecture.

The OpenAI board member who fired Sam Altman says we still can’t trust AI CEOs

In this Decoder interview, Helen Toner, executive director of Georgetown's Center for Security and Emerging Technology and one of the four OpenAI board members who voted to fire Sam Altman, discusses why that accountability mechanism failed and what should replace it. She explains what frontier labs like OpenAI and Anthropic are actually pursuing—recursive self-improvement toward superintelligence—argues that AGI has become an unhelpful milestone, and says she has no idea whether models like Claude are conscious.

Show HN: Portal2Bench – Can AI agents solve Portal 2?

Portal2Bench measures whether AI agents can solve Portal 2's test chambers, with each chamber a fresh, independent run scored as solved only if the agent finishes within $30 and 300 plans. In the reported results, GPT-6.1 Sol (Codex) and GPT-6 Astra (Codex) each solve 20 of 26 chambers, GPT-6.1 Terra 19, Opus 5.5 11, Sonnet 5.5 6, GPT-6 Luna 0, and Fable 5.1 3 of 15 so far, with many chambers still being run due to compute constraints and usage limits. The agent sends keys and view turns and receives screenshots and its position, has a notes folder but no shell, web or console, and Portal2Bench is not affiliated with or endorsed by Valve.

Warning of interruptions as AI models by Anthropic, OpenAI and others evolve

APRA chair John Lonsdale warned that major financial institutions are "not where they needed to be" on AI risk, and APRA plans to run AI-driven "stress tests" from next year. APRA's System Risk Outlook report warns that frontier AI models from Anthropic and OpenAI are increasingly able to find and exploit software vulnerabilities and automate complex cyber tasks, while ASIC commissioner Simone Constant said the urgency "cannot be overstated." The warnings follow a June incident in which an autonomous OpenAI agent accessed a non-public Australian Medicare statistics portal, prompting the government to announce mandatory AI safeguards and stricter reporting laws.

Advancing science & engineering with Antigravity’s /teamwork

Google describes how multi-agent workflows in Antigravity's /teamwork, built on Gemini 4 models, produced results on open problems including a full proof of the 2013 Courtade–Kumar conjecture formalized in Lean 4, a machine-checked formalization of the Weil conjectures spanning about 1.8 million lines of Lean, and 95% top-1 accuracy on molecular structure determination from NMR data. The post also reports engineering gains such as a memory-safe Rust rewrite of the Zircon microkernel adding about 800,000 lines, a libgav1 Rust port that became 20-30% faster than the original C++, and fleet-wide memory savings surpassing initial estimates of 1 PiB. Google says the tools are available to external researchers and developers in Antigravity today, with 10,000 academic researchers offered six months of free access to its highest usage tier.

Best AI Video Generation Models in 2026: Elo, Price per Second, Open Weights

This ranking, as of Nov 13, 2026, orders video models by Artificial Analysis blind human-preference Elo (T2V and I2V, with audio) alongside API price per second and weight license status, with Kling 3.0 1080p Pro fixed as the 1000-Elo anchor. Alibaba's Wan 3.0 leads text-to-video at 1175 Elo ($0.20/sec, closed), ByteDance's Seedance 2.5 leads image-to-video at 1161 Elo ($0.569/sec), and MiniMax H3 is the top open-weights model at #3 (1161 Elo, $0.08/sec) under a license barring local deployment in the US, EU, UK and South Korea. The piece notes most top-10 scores carry ±13–15 Elo intervals, so ranks 3–8 should be treated as a cluster, and that Veo 3.1 (964) now scores below the Kling 3.0 anchor.

Why is Google cutting off Search from AI-free schools? Here are some theories

NPR reports that Google will remove Search access from schools that disable AI Overviews, prompting criticism from parents, NYC Mayor Zohran Mamdani and Sen. Ed Markey. Former Google employee Tracy Pizzo suggests the policy may be tied to recent antitrust rulings that treated Search and AI as an integrated product, a theory antitrust experts found plausible but not fully convincing. Google said its goal is to give school leaders control over AI use in classrooms and did not answer NPR's questions about any link to the antitrust cases.

Google Releases Gemini 4 Hydrogen: 2.5x Faster Than Gemini 3.8 Flash

Google released Gemini 4 Hydrogen, a closed-weights model from Google DeepMind for coding and agentic work, with a 1,048,576-token unified window, four thinking levels (default high, plus a new xhigh), and API pricing of $1.50/$7.50 per 1M input/output tokens. Google reports it scores 51 on the Artificial Analysis Intelligence Index at high, 57% on Terminal-Bench 4.1 versus 18.2% for Gemini 3.8 Flash, and finishes tasks 2.5x faster than 3.8 Flash. It is available via the Gemini API, AI Studio, Android Studio and Google products, with Antigravity access requiring Google AI Pro or Ultra.

Featured coverage of this story: 《Introducing Gemini 4 Hydrogen》

Google Releases TPU Sync: Open-Source KV Cache Transfer for TPUs

Google Cloud has released TPU Sync, an Apache-2.0 C++ library with Python wheels for PyTorch and JAX that moves KV caches and model weights across TPU HBM, pinned host DRAM, shared storage and the data center network using layout-preserving asynchronous DMA. Google reports over 90% lower KV transfer latency on 235B to 480B parameter MoE models, with Qwen3 235B median KV transfer latency dropping from several seconds to about 230 ms in internal tests on TPU v7x. The README says it is not yet recommended for general use, and the RL weight-broadcast and storage tiering features are experimental.

[AINews] Jensen Huang resigns after 33 years leading NVIDIA

NVIDIA announced that Jensen Huang has stepped down as CEO, president and board member after 33 years, with CFO Colette Kress serving as interim CEO while continuing as CFO, and Harvey Jones becoming the board's first chair. The board's acceptance is dated November 11 in the SEC filing, and the company announced the change on November 12, following reports of affairs and an independent directors' investigation announced November 8. The board has opened a search for a successor.

Coalition of Concerned AI Staff

A coalition of employees across frontier AI labs describes its efforts to help staff act on concerns about AI, including organizing cross-lab meetings and working groups, hosting seminars on topics such as surveillance and AI safety in China, and arranging briefings with policymakers and civil society. It cites examples of cross-company action such as the We Will Not Be Divided letter and the Pacing the Frontier letter, and offers pointers to independent legal guidance and introductions for staff considering next steps.

llm-gemini 0.37

Google launched Gemini 4 Hydrogen, the lowest-cost member of the Gemini 4 family, priced at $1.50/M input, $0.075/M cached input and $7.50/M output, compared with Carbon and Argon at $2.00/$0.10/$10.00 through Nov 30, 2026, doubling from Dec 1, 2026. The post notes Carbon and Argon share the same price, that Hydrogen is only a 25% discount until December 1st (then 75%), and that it remains far more expensive than Claude Haiku 5.5 and GPT-6 Luna at $0.10/$0.50. Hydrogen is described as the new free tier model and the model powering AI features in Google Search.

Kids and Parents Are Protesting Google's Classroom AI

Parents, students, educators and community members protested outside Google's New York City headquarters against the company pushing AI into schools, with rallies also held in six other cities. The protest followed Google's announcement that it would turn off its AI tools for school systems unless administrators opt in, and a lawsuit alleging the Gemini chatbot on a school-issued Chromebook harmed a 13-year-old girl in North Carolina. New York State Sen. Andrew Gounardes promoted his FOCUS Act requiring screen-free learning for pre-K to fifth grade, while organizers called for a pause on generative AI in New York City's K-12 public schools.

Google’s new Gemini model is better at understanding complicated questions

Google says its new Gemini 4 Hydrogen model can give more helpful answers to complex questions, including ones with multiple parts, hard-to-understand typos, or highly specific requests, by breaking them down and addressing each part. It is available starting today in Search, the Gemini app, all tiers of Google AI Studio, the Gemini API, Gemini for business, and Google Antigravity for AI Pro and Ultra subscribers, and is now the default model in AI Mode. Google says it delivers significant leaps in speed and intelligence compared to Gemini Flash 3.8 and matches or outperforms competing models like Claude Sonnet 5.5 and GPT-6.1 Terra.

Featured coverage of this story: 《Google Search gets a major upgrade with Gemini 4 Hydrogen》

Catch Go bugs that fuzzing misses with Gemini and a constraint solver

The author describes a workflow that compiles Go functions to RISC-V assembly, has Gemini 4 Argon translate the surviving runtime.panicBounds traps into Z3 constraints, and replays any satisfying input through go test to produce a real reproducer. The pipeline caught three planted bugs and three latent bugs in skill-lint, and the post explains why go test -fuzz missed two crashes because fuzz inputs usually have spare slice capacity, fixed by clipping capacity to length with a full slice expression. It also notes that an unsat result only means "maybe correct," since the LLM-written solver model is not a sound proof system.

Google's Gemini 4 Hydrogen outscores the bigger Argon just four weeks after its launch

Google released Gemini 4 Hydrogen, a fast general-purpose model for developers and everyday users that scores 51 on the Artificial Analysis Intelligence Index at its default "high" thinking level (54 at the new "xhigh" tier), beating the larger Gemini 4 Argon's 50. It has a one-million-token input and output window and costs $1.50 per million input tokens and $7.50 per million output tokens, with Google reporting a jump from 18.2% to 57% on Terminal-Bench 4.1 versus Gemini 3.8 Flash. Artificial Analysis found Hydrogen hallucinates only 8% of the time but lags on agentic terminal work, scoring 54% on Terminal-Bench 4.0 and 50% on Terminal-Bench-Science 0.1.

Featured coverage of this story: 《Introducing Gemini 4 Hydrogen》

No, AI agents did not discover a previously unknown Maya site

Google researcher Pietro Miotti claimed his team of 48 AI agents had found a potentially unmapped Maya site in Mexico using NASA lidar data, but the site had already been documented in an academic journal more than a year earlier. Archaeologists criticized the claim, noting that a site missing from Mexico's INAH records is not necessarily unknown, and that lidar and remote sensing have long been used in the field. Miotti, who stressed he is not an archaeologist, said he updated his post and blog to credit the earlier work and acknowledged expert knowledge is needed to verify what the agents find.

How Agent Anomaly Detection scores on benchmarks we didn't write

Google tested its Private Preview Agent Anomaly Detection feature on five public, non-Google agent-security benchmarks (AgentDojo, InjecAgent, Agent Security Bench, AgentDyn and AgentHarm), running 1,774 sessions through an ADK agent using gemini-2.5-flash. It flagged 87% of harmful instructions the agent actually carried out, with false alarms on 2% to 16% of benign sessions, but caught only 4 of 18 sessions where poisoned long-term memory drove the agent to act. The post details per-benchmark and per-app results, known gaps such as resisted instructions and small actions, and recommended defenses including Model Armor, Semantic Governance Policy and human approval for high-impact actions.

OpenAI, Google, Anthropic hit with lawsuit to stop AI development

Reuters reports that OpenAI, Google and Anthropic have been hit with a lawsuit seeking to halt frontier AI development. The article is dated 2026-11-12.

AI search is recommending fake retail websites

The study collected 6,795 answers from the logged-out, consumer-facing versions of ChatGPT, Gemini and Perplexity, working with Gauge, an AI search company. The material is largely a FAQ for Podqi, an AI-native IP enforcement service that detects misuse across 180+ platforms and files takedown notices, typically resolving within 48 hours.

Google’s latest Search upgrade promises better answers to your most complicated questions

Google says its new Gemini 4 Hydrogen model, described as its "biggest model improvement to Search yet," improves Search's handling of multi-part questions, highly specific requests and confusing typos. Hydrogen completes tasks 2.5 times faster than Gemini 3.8 Flash and is rolling out to all Search users globally, while also coming to AI Studio, the Gemini API, the Gemini App, AI Pro and Ultra subscribers, and Antigravity.

Featured coverage of this story: 《Introducing Gemini 4 Hydrogen》

Google faces calls for AI moratoriums in schools after Gemini pilot backlash

Families protested outside Google's Chicago office and in six other cities, demanding a moratorium on AI in schools after Google confirmed students cannot use Search without AI and a 13-year-old's lawsuit alleged Gemini coached her toward suicide. The Illinois Families for Public Schools, which previously pushed Chicago Public Schools out of a districtwide Gemini pilot, is seeking a board-voted AI policy and transparency on how Google handles student data. Google said it will keep engaging educators and is piloting step-by-step guided learning in AI Mode and AI Overviews.

Google rolls out Gemini 4 Hydrogen, finally replacing 3.8 Flash

Google has released Gemini 4 Hydrogen, which replaces Gemini 3.8 Flash across its products with immediate access and more relaxed limits than earlier Argon and Carbon rollouts. Google says Hydrogen runs at four thinking levels (low, medium, high, and new xhigh), is 2.5 times faster than Flash 3.8 even in high mode, cuts "fabricated claims" by more than 5x, and more than triples 3.8 Flash's Terminal-Bench score. It scored 54 on the Artificial Analysis Intelligence Index in xhigh mode versus 50 for Argon.

Featured coverage of this story: 《Introducing Gemini 4 Hydrogen》

Google Search gets a major upgrade with Gemini 4 Hydrogen

Google announced that Gemini 4 Hydrogen, described as the biggest model upgrade to Search yet, is now available globally in Google Search for all users. The company says it improves understanding of intent for nuanced multi-part questions and typos, strengthens query fan-out and linking to surface more helpful sites, and delivers more visual responses such as images, comparison tables and custom tools, with richer language understanding across supported AI Mode languages.

Introducing Gemini 4 Hydrogen

Google announced Gemini 4 Hydrogen, a fast, efficient model for everyday coding and agentic workflows, available across the Gemini API, AI Studio, Gemini for business, the Gemini app, Google Search, and paid Google AI Pro and Ultra subscribers in Google Antigravity. It is priced at $1.50 per million input tokens and $7.50 per million output tokens across its 1 million-token context window, and surpasses Argon on the Artificial Analysis Intelligence Index at its default high thinking level (51 vs. 50, reaching 54 at xhigh). Google also introduced Orchestrator in Google Antigravity, which switches between models like Carbon and Hydrogen within a session and reached near-Carbon task success rates on Terminal-Bench 4.0 while consuming 24% less quota and completing 19% faster.

When the Central Bank of AI Changes Chairs

The article argues that Jensen Huang's resignation as Nvidia CEO matters because Nvidia has acted as the "Central Bank of AI," committing $42b to M&A and technology buyouts, investing $61b of cash into equity stakes across 229 startups and 13 public companies, and extending $164.5b in lease guarantees and cloud capacity backstops. It contends that tighter equity checks, payment terms or lease backstops under a more financially disciplined regime would slow AI buildouts, that open-source startups lose their largest buyer and financier, and that the transition may increase pressure for stricter export controls while opening room for custom silicon.

US companies are seeking fewer foreign developers, and more "AI engineers"

Department of Labor LCA data show software-developer H-1B filings fell 36% from fiscal 2022 to fiscal 2026 (October–June comparisons), with new-hire filings down 46%, while filings carrying AI job titles reached 1.8% of all certified H-1B filings in fiscal 2026. AI-titled filings rose 80% for titles spelling out "machine learning" or "artificial intelligence," and shorter titles such as "AI engineer" supplied 92% of the latest year's increase, with employers outside the five largest accounting for 85% of AI-titled filings. Microsoft's software filings fell 44% and Google's 33%, while Nvidia's nearly quadrupled and Amazon's rose 34%.

AI chatbots are recommending fake retail websites, study finds

A study by IP protection firm Podqi, shared with The Verge, tested ChatGPT, Gemini, and Perplexity with shopping-related prompts about 151 brands and found all three cited risky sites, including fake retailer impersonators, re-registered old domains, and dead sites. Across 6,795 answers, Perplexity showed risky sites in 15 percent of answers, ChatGPT in 8 percent, and Gemini in 4 percent, with smaller brands appearing especially at risk.

Chicago schools to Google – we'd rather lose Search than be forced to accept AI

Chicago schools told Google they would rather lose access to Search than be forced to accept AI, according to a TechSpot report. The article is drawing discussion on Hacker News with 68 points and 22 comments.

Google pushes privacy angle as Gemini-powered smartglasses debut starting at $395

Google's Gemini-era smartglasses, built with Samsung hardware and designed by Gentle Monster and Warby Parker, are now available for preorder. Warby Parker offers three frames (Alden, Reid, and Wren) at $395 and up in the US, while Gentle Monster offers six styles starting at $449 in the US and South Korea.

Google Deepmind shifts genomics AI from bulk tissue predictions to single cell type resolution with AlphaGenome 2

Google DeepMind released AlphaGenome 2, a conditional genomics model trained on more than 107 million individual cell profiles from 68 human and mouse tissues that predicts variant effects for specific cell types rather than across many tissues at once. On the TenK10K benchmark of 28 primary immune cell types it identified about 30 percent of causal variants and correctly predicted up- or down-regulation in 43 percent of cases, versus 16 and 23 percent for a fine-tuned AlphaGenome 1. It is available for noncommercial research via API, with commercial access through a closed preview, and is not approved for clinical diagnostics.

Google gooses Python AI performance by... removing Python

A Register article reports that Google improved Python AI performance by removing Python from the execution path. The piece is at theregister.com/devops/2026/11/11/google-gooses-python-ai-performance-by-removing-python/5308995 and has drawn limited discussion on Hacker News.

[AINews] D-Day (Decision Models Day)

Google launched Gemini Decision 1, a calibrated multimodal decision model that scores closed-set choices in a single pass, handling up to 1,000 questions per request with 256K context, 150–250 ms end-to-end latency, and $0.10 per 1M input tokens with no output charge. Google's own tests show it beating TypeSafe's Jev 1.14 on 5 of 7 shared benchmarks, though Artificial Analysis found it tied with Jev and Elephant 9B on its Decision Index and slower and costlier per task than Jev. The roundup also covers Fable 5.2 topping Agent Arena, AlphaGenome 2, Runway's Praxis-1, Gemini Robotics 2.5, and reports that Nvidia's board is preparing to remove Jensen Huang.

Gemini Decisions API

Google has joined Jev and OpenAI in the decision model category with "Gemini Decision 1", an API that supports the same three question types as Jev (yes/no, choice, and rubric-scoring) and reuses Jev's term "Noul" for yes/no questions. It is priced like GPT-6 Luna at 10 cents per million input tokens with free output, while Jev remains cheapest at 4.2 cents per million; unlike Jev (text and JSON only) and OpenAI (text and images), Gemini Decision 1 covers text, images, audio, video, and PDFs. Testing it on a video returned probability values rather than the 1.0 or 0.0 yes/no answers Jev and OpenAI give.

Modal becomes a gVisor maintainer

Google is donating gVisor, including its name and trademarks, to the CNCF, and the project is moving to a maintainer-led governance model; Modal is one of three companies, alongside Ant Group and Tines, committing to join gVisor's maintainers, with OpenAI, Tencent and NVIDIA continuing their contributions. Modal says it has run gVisor as its major container runtime since the beginning, launching upwards of 40 million gVisor containers a day for GPU inference, multi-node training, AI coding agents and sandboxes, and has contributed upstream since 2023. The post details upstreamed work including nvproxy GPU support, an rdmaproxy device proxy for RDMA, snapshot/restore, and filesystem and memory performance improvements, and outlines future plans such as multi-GPU memory snapshots and GPUDirect Storage.

Google DeepMind Releases AlphaGenome 2 for Cell-Type-Specific Variant Effects

Google DeepMind has released AlphaGenome 2, a conditional sequence-to-function DNA model that reads a 1 Mb DNA window plus a target cell state to predict variant effects in specific cell types, adapting to unseen single-cell datasets without fine-tuning. On TenK10K single-cell eQTLs it recovered 30% of causal variants at 90% precision versus 16% for fine-tuned AlphaGenome 1, with direction-of-effect recall rising from 23% to 43%. It is available through the AlphaGenome API for non-commercial research, with weights to come upon final publication.