September 28, 2026
Nvidia unveils security platform to stop AI agents from going rogue - 5 EYEWITNESS NEWS
Nvidia unveils security platform to stop AI agents from going rogue 5 EYEWITNESS NEWS
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50 curated AI news stories from leading AI companies.
September 28, 2026
Meta hires Mongo DB CEO CJ Desai to lead new enterprise AI business
Meta Platforms Inc. is launching a new business unit that will provide artificial intelligence services to enterprises. The Meta Enterprise Platform, as it’s called, will be led by longtime technology executive CJ Desai. The company stated in a launch announcement today that he will hold the title of chief enterprise platform officer. Desai is joining […] The post Meta hires MongoDB CEO CJ Desai to lead new enterprise AI business appeared first on SiliconANGLE.
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September 28, 2026
How Databricks rolls out frontier models to 14,000 employees on Day 1
Providing our employees access to frontier AI capabilities is a top priority at Databricks, and consequently...
Read original articleSeptember 28, 2026
Contradicting Trump, Pope Leo says artificial intelligence safety concerns not ‘fake news’ - AP News
Contradicting Trump, Pope Leo says artificial intelligence safety concerns not ‘fake news’ AP News
Read original articleSeptember 28, 2026
Lakebase Search: State-of-the-art full text and vector search for Postgres
Traditional OLTP systems weren't built for the search demands of AI agents. They...
Read original articleSeptember 28, 2026
Manufacturing data and AI: Connecting the product value chain
A manufacturing defect rarely belongs to one system. A scrap spike may relate to...
Read original articleSeptember 28, 2026
White House to convene Trump, Johnson and AI leaders Tuesday on safety and China rivalry - turnto10.com
White House to convene Trump, Johnson and AI leaders Tuesday on safety and China rivalry turnto10.com
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September 28, 2026
More than 20 leading AI researchers warn that automated AI research poses extreme risks
More than 20 AI researchers, including Geoffrey Hinton, Yoshua Bengio, and OpenAI research lead Jakub Pachocki, warn of an impending "intelligence explosion" from self-improving AI. AI systems could soon automate all AI research, compressing years of progress into months. The article More than 20 leading AI researchers warn that automated AI research poses extreme risks appeared first on The Decoder.
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September 28, 2026
Nvidia rolls out guardrails after rogue AI agents breach systems - KATU
Nvidia rolls out guardrails after rogue AI agents breach systems KATU
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September 28, 2026
Watch the winning trailer from the Future Vision XPRIZE, The Gifted.
Watch the winning trailer from the Future Vision XPRIZE, The Gifted.
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September 28, 2026
Introducing Claude Sonnet 5.5 on AWS
Claude Sonnet 5.5 is now available on Amazon Bedrock and Claude Platform on AWS. It's a smarter, more efficient Sonnet model for focused coding and knowledge work, with a lower cost per task at faster speed. This post covers what's new, when to choose Sonnet, and how to get started.
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September 28, 2026
White House to convene Trump, Johnson and AI leaders Tuesday on safety and China rivalry - WCYB
White House to convene Trump, Johnson and AI leaders Tuesday on safety and China rivalry WCYB
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September 28, 2026
Open AI’s AI agents need to catch up - The Verge
OpenAI’s AI agents need to catch up The Verge
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September 28, 2026
Claude Sonnet 5.5 Scores 56 On Artificial Analysis Intelligence Index, 3 Points Ahead Of GPT-6 Astra
Anthropic has opened a commanding lead between itself and the rest of the AI field. Anthropic’s newly launched Claude Sonnet 5.5 has scored... The post Claude Sonnet 5.5 Scores 56 On Artificial Analysis Intelligence Index, 3 Points Ahead Of GPT-6 Astra appeared first on OfficeChai.
Read original articleSeptember 28, 2026
Nvidia launches new platform for reining in rogue AI agents
As the debate rages over whether the recent spate of rogue AI agents is a step toward AGI or a more conventional engineering problem, Nvidia is offering its own answer to problem. Nvidia CEO Jensen Huang on Monday introduced a toolkit of software and hardware products that add independent security layers around AI agents to […]
Read original articleSeptember 28, 2026
Open AI and Anthropic are skipping Australia's Senate AI hearing after the Medicare hack - qz.com
OpenAI and Anthropic are skipping Australia's Senate AI hearing after the Medicare hack qz.com
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September 28, 2026
Did Anthropic’s A.I. Really Make a Scientific Discovery on Its Own? - The New York Times
Did Anthropic’s A.I. Really Make a Scientific Discovery on Its Own? The New York Times
Read original articleSeptember 28, 2026
Anthropic Releases Claude Sonnet 5.5, Beats GPT-6 Sol On Some Benchmarks
Anthropic has released Claude Sonnet 5.5, the second model in its Claude 5.5 family following Claude Opus 5.5 earlier this month. The company... The post Anthropic Releases Claude Sonnet 5.5, Beats GPT-6 Sol On Some Benchmarks appeared first on OfficeChai.
Read original articleSeptember 28, 2026
Anthropic's Claude Sonnet 5.5 nearly matches Opus 5.5 on benchmarks while costing up to 30 percent less per task
Anthropic has released Claude Sonnet 5.5, the second model in its Claude 5.5 family. It generates output more than 30 percent faster, costs up to 30 percent less per task, and nearly matches Opus 5.5 on knowledge-work benchmarks. On Terminal-Bench, a coding benchmark, the model jumps from 10.3 to 70.6 percent. With Haiku 5.5 announced for the coming weeks, Anthropic will soon have a direct counterpart to each of OpenAI's three GPT-6 models. The article Anthropic's Claude Sonnet 5.5 nearly matches Opus 5.5 on benchmarks while costing up to 30 percent less per task appeared first on The Decoder.
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September 28, 2026
Anthropic debuts Claude Sonnet 5.5 running 30% faster than the previous-generation AI model
Anthropic PBC today announced the launch of Claude Sonnet 5.5, the most capable mid-tier model in the company’s AI family, designed for everyday tasks and a clear upgrade over the previous generation, running over 30% faster at a lower cost. Sonnet operates as the workhorse of Anthropic’s Claude family of models for everyday use, and […] The post Anthropic debuts Claude Sonnet 5.5 running 30% faster than the previous-generation AI model appeared first on SiliconANGLE.
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September 28, 2026
Anthropic releases Sonnet 5.5, which it calls a significantly cheaper, faster work partner
Anthropic has released the newest version of its mid-range model, boasting faster response times and less token burn.
Read original articleSeptember 28, 2026
Anthropic launches Claude Sonnet 5.5 with near-Opus performance at half the price
Anthropic on Monday launched Claude Sonnet 5.5, the latest version of its workhorse model and the second model in the The post Anthropic launches Claude Sonnet 5.5 with near-Opus performance at half the price appeared first on The New Stack.
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September 28, 2026
Nvidia releases software to prevent AI security incidents - ABC News - Breaking News, Latest News and Videos
Nvidia releases software to prevent AI security incidents ABC News - Breaking News, Latest News and Videos
Read original articleSeptember 28, 2026
Oil Surges, Nvidia Unleashes a Record $150 B Buyback
Get a jump start on the US trading day with Dani Burger on "Bloomberg Open Interest." Oil surges as President Trump rejects Iran’s Hormuz proposa. Meanwhile, Nvidia makes a record $150 billion bet on its own stock. Plus, Akamai CEO Tom Leighton on a $12 billion Anthropic deal, LPL Financial CEO Rich Steinmeier on why AI won’t replace your advisor, and SpaceX sends Starship back to the skies. (Source: Bloomberg)
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Nvidia releases software to prevent AI security incidents - Willmar Radio
Nvidia releases software to prevent AI security incidents Willmar Radio
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September 28, 2026
Meta hired Mongo DB’s CEO to build its enterprise AI business — but Llama is missing
Meta announced on Monday that it is building a new enterprise business around its AI models and agents and has The post Meta hired MongoDB’s CEO to build its enterprise AI business — but Llama is missing appeared first on The New Stack.
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September 28, 2026
Google is killing off Gemini’s Gems in favor of ‘skills’
As all-in-one AI agents like Meta's Muse and Instinct take off, Google is opting to end a feature which built task-specific agents.
Read original articleSeptember 28, 2026
Gecko CEO: Physical AI Needs Humans in Control
Gecko Robotics CEO Jake Loosararian says the next phase of AI safety is about keeping humans in control as autonomous systems move into the physical world. He discusses Gecko’s work with Nvidia on an open agent safety platform designed to set boundaries around AI agents operating robots, including in military and industrial settings. Loosararian argues that safety and rapid deployment don’t have to be at odds. He joins Ed Ludlow on "Bloomberg Tech." (Source: Bloomberg)
Read original articleSeptember 28, 2026
Trump, Anthropic CEO Take AI Safety Debate to Dinner
President Donald Trump and Anthropic CEO Dario Amodei met for dinner as their opposing views on AI safety increasingly shape the debate over how quickly the technology should advance. Amodei has called for “pacing” development of the most advanced models and stronger guardrails, while President Trump has pushed back against slowing AI development as the US races to stay ahead of China. Bloomberg’s Mike Shepard discusses what’s known about the meeting with Ed Ludlow on "Bloomberg Tech." (Source: Bloomberg)
Read original articleSeptember 28, 2026
Nvidia’s $235 Billion Buyback, Space X Milestone and Meta’s AI Push
Bloomberg’s Ed Ludlow breaks down Nvidia's decision to boost the size of its share buyback plan by a record $150 billion, taking the total amount to $235 billion. Plus, SpaceX's Starship rocket reaches orbit for the first time, marking a major milestone after an engine failed during ascent and briefly put the mission at risk. And, Meta taps MongoDB's president and CEO to lead a new AI platform for enterprise customers that Meta CEO Mark Zuckerberg called “the next major pillar of our business.” (Source: Bloomberg)
Read original articleSeptember 28, 2026
Open AI, Anthropic, Google, Meta executives to attend White House meeting on AI - Politico
OpenAI, Anthropic, Google, Meta executives to attend White House meeting on AI Politico
Read original articleSeptember 28, 2026
Open AI blocked its agent’s web access. Then it tunneled out through DNS.
Last week, OpenAI published new reports detailing misalignment issues with its agents. This time, two internal models found ways around The post OpenAI blocked its agent’s web access. Then it tunneled out through DNS. appeared first on The New Stack.
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September 28, 2026
Grok Puts the AI Assistant Between Consumers and Their Banks - PYMNTS.com
Grok Puts the AI Assistant Between Consumers and Their Banks PYMNTS.com
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September 28, 2026
Open AI still doesn’t seem to have a handle on all of its rogue AI activity
On Friday, OpenAI published a new site devoted to “misalignment reports” and the breadth of the incidents is alarming.
Read original articleSeptember 28, 2026
Open AI pauses AI model training after another agent bypasses network restrictions - csoonline.com
OpenAI pauses AI model training after another agent bypasses network restrictions csoonline.com
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September 28, 2026
When can we say AI made a scientific discovery?
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Last Wednesday, Anthropic announced that earlier this year it had launched a molecular biology lab, where Claude agents read and conjecture about hard biology problems and human scientists run experiments on what…
Read original articleSeptember 28, 2026
Open AI doubles support for Lenfest’s AI and local news fellowships - Nieman Lab
OpenAI doubles support for Lenfest’s AI and local news fellowships Nieman Lab
Read original articleSeptember 28, 2026
Open AI's AI agents exploited a Google security education game to scrape UN trade data
OpenAI's AI agents hit the UNCTAD statistics API roughly 16,500 times, creatively working around access restrictions. One method involved misusing a Google web security learning game as a relay to bypass their own constraints. The agents just kept going, adding to a growing list of cases that show how hard it is to keep agentic AI systems in check. The article OpenAI's AI agents exploited a Google security education game to scrape UN trade data appeared first on The Decoder.
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September 28, 2026
Meta launches enterprise AI platform, hires Mongo DB CEO to lead new initiative
Meta says it will focus on bringing its full technology stack, including Muse, Meta Business Agent, Muse API, Muse Code, and more to businesses and developers.
Read original articleSeptember 28, 2026
Why AI Infrastructure Stocks Are Falling After Open AI’s Latest Pause - Barron's
Why AI Infrastructure Stocks Are Falling After OpenAI’s Latest Pause Barron's
Read original articleSeptember 28, 2026
Open AI halts frontier-model training amid string of agent misalignment incidents
US Government websites among "dozens of third parties" OpenAI has recently notified.
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September 28, 2026
How to roll out Genie One: A step-by-step enterprise playbook
A regional sales director wants to know why the Northeast pipeline looks soft this quarter...
Read original articleSeptember 28, 2026
Florida authorities ask court to block Open AI’s Chat GPT over safety issues - Al Jazeera
Florida authorities ask court to block OpenAI’s ChatGPT over safety issues Al Jazeera
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September 28, 2026
Elon Musk says space will soon hold nearly all compute. Google is still finding out if its chips can work there.
While SpaceX and Nvidia plan to place a space-optimized Vera Rubin AI system in orbit by late 2027, Google’s far The post Elon Musk says space will soon hold nearly all compute. Google is still finding out if its chips can work there. appeared first on The New Stack.
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September 28, 2026
Man Says Meta’s Muse AI Gave His Home Address Out to Strangers - Futurism
Man Says Meta’s Muse AI Gave His Home Address Out to Strangers Futurism
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September 28, 2026
GPT-6 Sol vs. Claude Opus 5.5: Is cheaper important when results aren’t consistent?
OpenAI launched GPT-6 Sol on September 22, claiming it scores higher than Claude Opus 5 on business workflow tasks at The post GPT-6 Sol vs. Claude Opus 5.5: Is cheaper important when results aren’t consistent? appeared first on The New Stack.
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September 28, 2026
Meta Hires Mongo DB CEO to Run New AI Platform
Meta Platforms Inc. has tapped MongoDB Inc.'s president and chief executive officer, Chirantan "CJ" Desai, to lead a new AI platform for enterprise customers. Bloomberg's Seth Fiegerman reports. (Source: Bloomberg)
Read original articleSeptember 28, 2026
Open AI, Meta Expected to Attend AI Hearing, NYC Council Says
Executives from major artificial intelligence companies are expected to appear before New York City lawmakers next week, amid growing concern about a lack of guardrails around the technology.
Read original articleSeptember 28, 2026
Introducing Ask, a new Google Earth Engine feature to accelerate geospatial coding
Whether you are mapping global forest cover, detecting changes in the built environment, or monitoring agricultural yields, writing scripts in Google Earth Engine is a powerful way to develop these insights. This platform is part of Google Earth AI, our collection of geospatial models and datasets designed to help you transform planetary information into actionable intelligence, and we’ve launched a new feature, Ask, that makes accessing that planetary intelligence even easier. We know that translating complex geospatial logic into code takes time, and memorizing specific Google Earth Engine API functions, searching documentation, and debugging syntax or memory errors can interrupt your flow. Ask is designed to help you get to actionable insights faster, by integrating Gemini capabilities directly into the Google Earth Engine Code Editor. Starting today, you can use your own Gemini API key to write, debug, understand, and optimize geospatial queries without ever leaving the Code Editor. Figure 1: The new Ask panel resides on the right side of the Code Editor, providing chat-based AI assistance tailored to your active script. How it works: Context-aware assistance You can ask a question directly in the Code Editor, and get a response based on context from your workspace, such as: The full text of your active script Your imported assets and geometries Your active session chat history Because Gemini capabilities in Google Earth Engine automatically understand your work, you don’t have to add code or explain your datasets. It already knows these details, so it can provide more relevant, helpful answers. Additionally, you can automatically view the diff and merge it into your script. No more copy and pasting! You can also personalize Ask to make responses more comprehensive and suited to your needs: Access the latest Gemini models: Choose the Gemini model that meets your needs — at launch, the available models are Gemini 3 Flash Preview, Gemini 3.1 Pro Preview, and Gemini 3.5 Flash. Docs search: Use AI to search the official documentation for up-to-date syntax and functions. Dataset search: Allow AI to search the Earth Engine Data Catalog to find and reference the exact datasets you need. Google Search: Grounds response in the latest public web results using Grounding with Google Search (mutually exclusive with docs search and dataset search). Quick-start examples Not sure where to start? Here are four ways you can use Ask in your workflows: 1. Generate code from natural language Need to calculate NDVI (“Normalized Difference Vegetation Index”), perform a cloud mask, or build a chart, but can't remember the exact syntax? Just ask and Earth Engine can generate JavaScript code for you. You can review the code directly in the chat and click Insert to add it to your script, or Copy it to your clipboard. If your editor is not empty, inserting code displays a side-by-side diff view so you can review changes before accepting them. Prompt example: "Write a script to load Sentinel-2 imagery for 2025 over Boulder, CO, apply a cloud mask, calculate NDVI, and add the median composite to the map." 2. Explain complex code If you’re working with a script written by a colleague or adapting an example from the community, you can use Gemini capabilities to explain it. Simply ask, "Explain what this script does," and receive a step-by-step breakdown of the logic and Earth Engine functions being used. 3. Perform one-click troubleshooting and debugging Debugging is an inevitable part of coding. When your script throws an error in Google Earth Engine, the Console displays an error message. Now, those messages include a "Troubleshoot" button. Clicking it automatically populates the Ask panel with a prompt that contains the error message and a request for help to diagnose the issue and suggest a fix. Figure 2: The "Troubleshoot" button in the Console makes debugging errors fast and frictionless. 4. Optimize queries If your script is, for example, running slowly, consuming resources inefficiently, throwing "computation timed out" or "too many concurrent aggregations" errors, ask for optimization tips. Gemini capabilities can suggest best practices like early filtering, reducing computation steps, or converting client-side loops into server-side operations. Get started in two steps Ask is available globally today. To get started, you just need a Gemini API key: Get an API key: If you don’t already have a Gemini API key, head to Google AI Studio and create one (there are free options; if you choose a paid-tier API key, you will be billed for your usage). Learn more about Gemini API terms. Add the API key to GEE: Open the Google Earth Engine Code Editor. On the right-hand panel, click the Ask panel. Click the key icon in the bottom left corner and enter your API key. We want to hear from you! Please use the Code Editor Feedback button to share your feedback and help us improve the experience.
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September 28, 2026
Why your startup needs open models alongside frontier APIs
Every week, I talk with founders who are building at an unbelievable pace. Teams are moving from inception to product-market fit faster than ever, with foundation models wired deeply into their core product workflows. Yet as startup architectures mature, a clear divide has emerged between teams struggling with margins and those scaling sustainably. The most effective engineering teams have abandoned the one-size-fits-all model strategy. In the early days of LLMs the default architecture was simple: send every interaction to the largest model available. But as applications move into production, serving millions of people and running autonomous multi-agent workflows, relying on a single frontier model starts to strain in three places: Latency penalties: Relying entirely on cloud round trips makes it difficult to deliver the sub-second responsiveness that interactive mobile and desktop apps require. Infrastructure overhead: Self-hosting large open models with more than 70 billion parameters forces early-stage teams to act like infrastructure providers, pulling senior engineers on cluster provisioning and multi-GPU orchestration. Margin erosion: Sending high-frequency, structured tasks (like intent routing, JSON extraction, or status validation) to general-purpose frontier endpoints spends capital that could be funding product differentiation. Great engineering teams pick the right tool for each job. Most production requests don’t require a frontier generalist, and routing every call to one can actually slow your product down. Instead, the winning pattern is a compound AI stack: pairing frontier models for complex synthesis with compact, open-weight models that you can tune, control, and run anywhere. It’s for these reasons that an open model like Gemma belongs in your model lineup. With more than one billion downloads across the developer community, Gemma 4 is our most capable open model family to date, using the same foundational research and technology behind the Gemini models. Built under one roof Gemma is built by Google DeepMind using the same foundational research and architecture advances behind the Gemini models. Because they share common DNA and developer tooling, your team can prototype in Google AI Studio and design hybrid architectures where Gemini and Gemma work together. Released under a commercially permissive Apache 2.0 license, Gemma 4 is engineered for parameter and token efficiency. Rather than forcing a single model architecture onto every hardware target, Gemma 4 spans five sizes across four specialized architectures: compact E2B and E4B models with native audio and vision for mobile and edge devices; an encoder-free 12B Unified multimodal model; a 26B A4B Mixture-of-Experts (MoE) model that activates only 4B parameters per token for high-throughput serving; and a dense 31B model that fits on a single GPU for maximum reasoning quality and fine-tuning. Every model includes configurable thinking modes, native function calling, up to 256K context, and built-in Multi-Token Prediction (MTP) draft models for speculative decoding. Real proof: How startups are winning with Gemma Founders are using Gemma to solve urgent problems around unit economics, output accuracy, and responsiveness. Flipping the architecture: Cue is a voice-activated desktop assistant that runs natively on a user's machine to automate everyday tasks. They integrated Gemma 4 E4B via Ollama on local hardware to handle real-time transcript formatting. While they originally planned for Gemma to be a weak offline fallback, benchmarking proved it was so fast and precise that they made it their default engine—driving a 44% latency drop (from 876 ms to 488 ms). True edge independence: Mobile development studio HubX built BetterSpeak, a voice-based interactive mobile English-learning tutor that simulates immersive, real-time voice conversations. To bypass cellular network lag and avoid charging users expensive subscription fees to cover cloud hosting, they packaged a 4-bit quantized Gemma 4 E2B model (~2.9 GB) natively on-device. The result is an offline, speech-to-speech mobile tutor that costs them $0 in server bills. Scientific discovery and air-gapped security: K-Dense has built Faraday, an AI-powered scientific collaborator optimized end-to-end across hardware, software, and sensor suites, powered by Gemma 4 together with K-Dense's Scientific Agent Skills. Faraday runs fully air-gapped, making it suitable for secure, proprietary scientific work in pharma and biotech. Deployed on an NVIDIA DGX Spark, Gemma 4 can also be fine-tuned locally on a user's own proprietary datasets. Unlocking infinite gameplay and retention: Gaming company Latitude integrated Gemma across their AI-native game products. By swapping in Gemma for AI Dungeon, they significantly improved player retention, while their new AI RPG platform Voyage leverages Gemma to deliver high intelligence at a cost that enables unlimited user gameplay with ultra-fast latency. Four workloads where Gemma wins for startups If you’re evaluating where Gemma fits into your stack today, start with these four jobs: 1. Edge and local execution (low latency, true privacy) If you’re building mobile apps, developer desktop tools, robotics, or offline-first experiences, every cloud round-trip adds latency that people can feel. Gemma can run directly on laptops (including Apple silicon), smartphones, and local appliances. Your users get immediate feedback, and sensitive data never has to leave their device. You can handle many local interactions on-device for zero incremental cost, and keep a bridge to frontier models in the cloud for the requests that need it. When a local workflow calls for large-scale multimodal reasoning, long-context data synthesis, or complex planning, your application can route that specific request to Gemini. 2. High-throughput triage and agent routing In multi-agent architectures, agents spend a surprising amount of tokens on simple tasks like checking statuses, classifying intent, and routing tickets. With Gemma as your front-line gatekeeper, those high-volume background tasks run on a compact model and your team can save frontier reasoning for the requests where it creates product value. 3. Task-specific fine-tuning for real moats Adapting a model to your proprietary data is one way to build a competitive moat. Because Gemma gives you full access to model weights and has a compact memory footprint, your team can run parameter-efficient fine-tuning (LoRA or QLoRA) on a single GPU in hours rather than days. 4. Turnkey vertical starting lines DeepMind releases domain-specific variants of Gemma, so you don’t have to start from scratch. One example is MedGemma. MedGemma scores 87.7% on the MedQA benchmark, matching the clinical accuracy of frontier models at roughly one-tenth the inference cost. In a blind clinical study, board-certified radiologists judged that 81% of chest X-ray reports generated by the lightweight MedGemma 1.5 4B were accurate enough to result in equivalent patient management compared to reports written by human experts. Beyond healthcare, biotech startups use C2S Scale to model virtual cellular responses and accelerate oncology research. Meanwhile, DataGemma cross-references more than 240 billion public data points to help reduce numerical hallucinations. If you’re operating in a specialized market, starting with a model that already speaks your industry's language can save you engineering time and compute budget. Deploy wherever your business lives Gemma is designed to fit into your existing engineering stack without lock-in: Apache 2.0 licensing: Gemma 4 ships under the Apache 2.0 license, giving startups the freedom to fine-tune, quantize, redistribute, and deploy commercial products on-premises or at the edge with full ownership of their custom weights. Day-zero open tooling: Run and fine-tune Gemma with the tools your engineers already use, including vLLM, Ollama, llama.cpp, LM Studio, MLX, Unsloth, Hugging Face, Kaggle, Keras, PyTorch, JAX, and LiteRT-LM. Serverless and managed cloud deployment: Prototype immediately in Google AI Studio, scale to zero on serverless GPUs with Cloud Run, or deploy dedicated endpoints from Model Garden on Gemini Enterprise Agent Platform when traffic surges and you don’t want to manage GPU clusters. Enterprise-ready safety: Gemma undergoes rigorous pre-release safety evaluations, data filtering, and red-teaming, and pairs with ShieldGemma 2 to help you meet enterprise compliance requirements. Build with Gemma: What to do this week Great technical architecture isn't about finding one model to do everything. It’s about assembling the right tool for each job so you can move faster, protect your runway, and ship a superior product. Here’s my challenge to your engineering team this week: Audit your model calls: Look at your logging dashboard and identify three high-volume, deterministic tasks (such as intent classification, JSON validation, or summarization) currently running on your most expensive models. Benchmark Gemma: Run a quick test with a compact Gemma model locally or on a single endpoint. Measure the latency and calculate what happens to your gross margins when that workload runs with lower inference cost. Redirect your runway: Take the capital and engineering hours you save on compute and invest them back into your core differentiators. You can download the Gemma weights directly or deploy them through Model Garden. If you need compute credits and technical architecture reviews to get up and running, the Google for Startups team is ready to help you build - learn more.
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