News from the AI & ML world
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Google has launched Gemini CLI (command line interface), a terminal-based version of its AI assistant. This new tool allows users to interact with Gemini through a command line, offering a generous free tier of up to 60 model requests per minute and 1,000 per day. The Gemini CLI is designed to cater to developers and other users who prefer a command-line interface for coding assistance, debugging, project management, and querying documentation. It supports various operating systems, including Mac, Linux (including ChromeOS), and Windows, with a native Windows version that doesn't require WSL.
Google’s Ryan Salva highlighted the "unmatched usage limits" of Gemini CLI, which includes a 1 million token context window and use of the Gemini 2.5 Pro LLM. The CLI also integrates with the gcloud CLI, suggesting Google's intent to encourage developers to deploy applications to Google Cloud. While there is a free tier, a paid option that uses an AI Studio or Vertex API key exists. It unlocks additional features such as policy and governance capabilities, choice of models, and the ability to run agents in parallel, while removing the requirement to use Gemini activity to improve Google’s products. The tool is open source on GitHub under the Apache 2.0 license. Verizon has integrated a Google Gemini-based chatbot into its My Verizon app to provide 24/7 customer service. The company claims to be seeing accuracy "north of 90 percent" with the bot, however this means up to 10% of responses are not accurate. David Gerard mentions an example of Personal Shopper, where random items are added to bills. Verizon's CEO, Sowmyanarayan Sampath, stated that AI is the answer to customer churn after a price increase in the first quarter of 2025. Recommended read:
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@techstrong.ai
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Amazon is making a substantial investment in artificial intelligence infrastructure, announcing plans to spend $10 billion in North Carolina. The investment will be used to build a cloud computing and AI campus just east of Charlotte, NC. This project is anticipated to create hundreds of good-paying jobs and provide a significant economic boost to Richmond County, positioning North Carolina as a hub for cutting-edge technology.
This investment underscores Amazon's commitment to driving innovation and advancing the future of cloud computing and AI technologies. The company plans to expand its AI data center infrastructure in North Carolina, following a trend among Big Tech companies who are building out infrastructure to meet escalating AI resource requirements. The new "innovation campus" will house data centers containing servers, storage drives, networking equipment, and other essential technology. Amazon is also focused on improving efficiency by enhancing warehouse operations through the use of AI. The company unveiled AI upgrades to boost warehouse efficiency. These upgrades center around the development of "agentic AI" robots. These robots are designed to perform a variety of tasks, from unloading trailers to retrieving repair parts and lifting heavy objects, all based on natural language instructions. The goal is to create systems that can understand and act on commands, transforming robots into multi-talented helpers, ultimately leading to faster deliveries and improved efficiency. Recommended read:
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@techstrong.ai
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Amazon is making a significant push into robotics with the development of humanoid robots designed for package delivery. According to reports, the tech giant is working on the AI software needed to power these robots and is constructing a dedicated "humanoid park" at its San Francisco facility. This indoor testing ground, resembling the size of a coffee shop, will serve as an obstacle course where the robots can practice the entire delivery process, including navigating sidewalks, climbing stairs, and handling packages. The initiative reflects Amazon's continued efforts to enhance efficiency and optimize its logistics operations through advanced automation.
Amazon envisions these humanoid robots eventually riding in its Rivian electric vans and independently completing the last leg of the delivery journey. The company is reportedly testing various robot models, including the Unitree G1, and focusing on developing AI software that will allow them to navigate real-world environments. This move comes as Amazon continues to invest heavily in AI and robotics, including the deployment of over 750,000 robots in its warehouses. The integration of humanoid robots into the delivery process has the potential to reduce physical strain on human workers and address labor shortages, especially during peak seasons. This initiative is part of a broader trend of leveraging AI and robotics to optimize supply chains and reduce operational costs. While there is no official rollout date for the humanoid delivery robots, Amazon's investment in this technology signals its commitment to exploring innovative solutions for package delivery. Furthermore, it coincides with Amazon investing $10 billion in North Carolina to build new data centers as part of a massive AI infrastructure expansion. Recommended read:
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@cloud.google.com
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Google Cloud is enhancing its AI Hypercomputer to accelerate AI inference workloads, focusing on maximizing performance and reducing costs for generative AI applications. At Google Cloud Next 25, updates to AI Hypercomputer's inference capabilities were shared, showcasing Google's newest Tensor Processing Unit (TPU) called Ironwood, designed for inference. Software enhancements include simple and performant inference using vLLM on TPU and the latest GKE inference capabilities such as GKE Inference Gateway and GKE Inference Quickstart. Google is paving the way for the next phase of AI's rapid evolution with the AI Hypercomputer.
Google's JetStream inference engine incorporates new performance optimizations, integrating Pathways for ultra-low latency multi-host, disaggregated serving. The sixth-generation Trillium TPU exceeds throughput performance by 2.9x for Llama 2 70B and 2.8x for Mixtral 8x7B compared to TPU v5e. Google’s JAX inference engine maximizes performance and reduces inference costs by offering more choice when serving LLMs on TPU. JetStream throughput is improved, achieving 1703 token/s on Llama 3.1 405B on Trillium. Google is also intensifying its efforts to combat online scams by integrating artificial intelligence across Search, Chrome, and Android. AI is central to Google's anti-scam strategy, blocking hundreds of millions of scam results daily and identifying more fraudulent pages. Gemini Nano provides instant detection of high-risk websites, helping counter new and evolving scams across platforms. Google has long used AI to detect and block scams, including fake tech support, fraudulent financial services, and phishing links. Recent updates to AI classifiers now allow the company to detect 20 times more scam pages, improving the quality of search results by reducing exposure to harmful sites. Recommended read:
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