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Want a humanoid, open source robot for just $3,000? Hugging Face is on it.

Hugging Facejust pulled the curtain back onHopeJR, a humanoid robot that swings 66 degrees of freedom—at just$3,000. This price tag shames the $16,000 slapped on Unitree's G1. Together with The Robot Studio, they've created this robot with a dash of Bender's charisma. The kicker? It's fully open-sou.. read more  

Want a humanoid, open source robot for just $3,000? Hugging Face is on it.
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Why GCP Load Balancers Struggle with Stateful LLM Traffic — and How to Fix It

Deploying LLMs onGCP Load Balancersis like fitting a square peg in a round hole. These models aren't stateless, so skip HTTP, go straight forTCP Load Balancing. Toss in Redis to keep those sessions on a leash. Tweak load balancer settings to dodge mid-stream socket calamities. Embrace the power ofGK.. read more  

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LLMOps: DevOps Strategies for Deploying Large Language Models in Production

LLMOpsshakes up the MLOps scene with tailor-made Kubernetes magic. It wrestlesGPU scheduling, caching, and autoscalingfor those behemothLLM deployments. Keep an eye out for serverless endpoints and model meshes—smooth scaling and a wallet-friendly operation... read more  

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It’s not your imagination: AI is speeding up the pace of change

AI takes a victory lap:Mary Meeker revealsChatGPTsnagged 800 million users in a brisk 17 months. Meanwhile, the bean counters cheer as inference costs nosedived 99% in just two years. Profitability? That's still a cliffhanger... read more  

It’s not your imagination: AI is speeding up the pace of change
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Perplexity offers training wheels for building AI agents

Perplexity Labsis your quick-draw tool for crafting apps and digital delights, powered by LLMs likeGPT-4 Omni. It’s a star where others stumble: fast, project-driven tasks. Expect example-heavy insights and real-world project demos. While competitors dawdle, it delivers. Need deep web browsing, code.. read more  

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Using AI to outsmart AI-driven phishing scams

Phishing scamsare growing craftier, employing AI likeFraudGPTto weave through filters and masquerade as real emails, boosting scam rates by70%. AI can unveil sneaky phishing patterns humans miss, but it loves a good panic. It often cries wolf with false alarms and needs a babysitter to adjust to eve.. read more  

Using AI to outsmart AI-driven phishing scams
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We rewrote large parts of our API in Go using AI: we are now ready to handle one billion databases

Tursooverhauled its API withGoand AI, gunning for 1 billion databases. Think big, act smart. They squeezed every byte by adopting string interning. No more in-memory maps—they swapped them for aSQLite-backedLRU cache. The result? Leaner memory usage and hassle-free proxy bootstrapping... read more  

We rewrote large parts of our API in Go using AI: we are now ready to handle one billion databases
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From Zero to Hero: Build your first voice agent with Voice Live API

TheVoice Live APIditches the clutter of juggling models. One API call, and voilà—real-time,natural-sounding bots. It’s harnessed over WebSocket, keeping everything sharp and efficient... read more  

From Zero to Hero: Build your first voice agent with Voice Live API
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A visual introduction to vector embeddings

OpenAI's text-embedding-ada-002often gets a peculiar itch at dimension 196—vectors peaking awkwardly there. Entertext-embedding-3-small, swooping in to smooth out the distribution. Now, ontosimilarity metrics. For unit vectors, the dot product is your fast friend. It's interchangeable with cosine si.. read more  

A visual introduction to vector embeddings
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AI agents have access to key data across the enterprise

82% of organizations have AI agents on deck; a mere 44% bother with security policies.That leaves a lot of open doors. A staggering 96% of tech pros are side-eyeing these agents as ticking time bombs, yet 98% plan to unleash more. It's like setting out catnip for hackers. These agents wield power wi.. read more  

AI agents have access to key data across the enterprise
Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.