The AI frontier just got more tangible, technical, and transformative than ever. Stream reimagines creativity through voice and gesture, AWS unlocks trillion-scale intelligence with elastic compute, and Google’s DS-STAR automates the data science workflow from query to code—each redefining how humans think, build, and scale with AI.

💭 Stream: Turn Thoughts Into Action Instantly – Stream introduces a conversational AI companion and the Stream Ring, a gesture-driven wearable for hands-free idea capture and media control. With touch-activated voice input, haptic feedback, and offline access, it bridges thought and action seamlessly—ushering in a new era of mindful creativity.

⚙️ AWS EFA: Powering Trillion-Parameter Models – AWS’s Elastic Fabric Adapter enables trillion-parameter Mixture-of-Experts (MoE) models to train and deploy efficiently using multi-GPU parallelism. By optimizing data, tensor, pipeline, and expert layers, AWS makes large-scale AI models faster, more accessible, and production-ready at unprecedented scale.

📊 Google DS-STAR: The AI Data Scientist – Google’s DS-STAR agent turns natural language queries into verified Python workflows, handling structured and unstructured data across CSV, JSON, Markdown, and text. Its iterative reasoning and LLM-based verification outperform existing solutions, making automated, reliable data science a reality.

From wearable creativity to trillion-scale compute and autonomous analysis, AI’s next chapter isn’t just smarter—it’s embodied, distributed, and deeply integrated into how we think and create.

Turn Thoughts Into Action Instantly

Stream is a conversational tool that extends your own thinking, letting you capture and build ideas effortlessly. Its companion device, the Stream Ring, allows hands-free note-taking and music control with simple gestures—hold to speak, tap to interrupt, double tap to skip, and swipe for volume. Built with aluminum and resin materials, it’s water resistant and connects via Bluetooth. The ring includes a voice-capture mic activated only by touch and delivers haptic feedback for confirmation. It supports iOS, ships in the U.S. starting Summer 2026, and comes in matte silver or polished gold, priced at $249 with a 3-month Pro subscription. Users can switch to a free tier anytime, and all data remains accessible offline. The Stream experience blends voice, gesture, and haptics to make capturing thoughts feel natural. Designed as a seamless self-extension, it encourages mindful creativity anywhere. Limited units are available, with refundable preorders now open for early adopters.

Trillion-Parameter AI Models Go Live on AWS

Enabling Trillion-Parameter Models on AWS EFA" discusses how modern AI models with up to a trillion parameters, such as Mixture of Experts (MoE) models, are trained and deployed efficiently using AWS Elastic Fabric Adapter (EFA) technology. MoE models improve transformer layers by routing data to specialized expert sub-networks, which reduces computational loads and increases scalability. AWS EFA allows these massive AI models to run across multiple GPUs with optimized parallelism methods including data, tensor, pipeline, and expert parallelism. This infrastructure supports large-scale AI workloads with better throughput and user interactivity, making it possible to deploy trillion-parameter models for advanced tasks in AI research and applications. The combination of AWS hardware and software advancements enables organizations to explore and operationalize these highly complex models with just a few lines of code. This marks a significant step in the accessibility and performance of next-generation AI systems.

Google’s DS-STAR Transforms Data Science with AI

Google's DS-STAR is a cutting-edge versatile data science agent designed to automate complex data science workflows by converting natural language queries into executable Python code. Unlike previous agents limited to structured data, DS-STAR can analyze and extract context from varied and unstructured data formats such as CSV, JSON, Markdown, and text files. It operates in an iterative cycle of planning, coding, and verification using multiple AI agents, including a verification step with an LLM-based judge to ensure solution quality. DS-STAR outperforms existing state-of-the-art methods on key data science benchmarks by efficiently handling heterogeneous datasets and continuously refining its plans until accurate insights are produced. This advancement helps make data science more accessible and efficient across diverse real-world applications.

Hand Picked Video

In this video, we'll take a closer look at Perplexica, the perfect replacement for Perplexity AI.

Top AI Products from this week

• Dazl - Dazl combines generative AI with hands-on editing tools. Build apps, then refine every detail through chat, visual panels, or code. Get full visibility into how your product is built and the control to edit until it’s exactly how you imagined.

• Ancher - DMost feeds keep you scrolling — filled with algorithmic junk, drug-like short videos, and endless echo chambers. Ancher, instead, keeps you growing. It helps you anchor what matters.

• Golf - Golf Firewall is the security layer for companies exposing MCP servers. It protects your MCP server from serving malicious or sensitive data - blocking prompt injections, PII leaks, and credential exposure before they reach customer agents.

• Elfsight - Elfsight’s no-code AI widgets help your website engage, assist, and convert visitors 24/7. From human-like chatbots to calculators you can build with a single prompt — get better results with less effort.

• UGC Ads in Any Language - Create engaging, authentic UGC-style videos with UGC AI Video Generator. Perfect for marketing, social media, and product demos. Generate professional, user-generated content in any language, in just minutes, all at a fraction of the usual cost.

• LLM Session Manager - The first monitoring platform for AI coding tools. Real-time health scoring, team collaboration, AI-powered insights, and cross-session memory. Track token usage, prevent session failures, and build organizational knowledge. 100% free & open source.

This week in AI

• AI Data Silos Your Biggest Threat - AI magnifies risks by exploiting data silos and vendor lock-ins. High API fees block data access, fueling costly AI vendor control and stifling innovation. Control your data or be controlled.

• Kosmos AI Scientist Revolution - Kosmos accelerates scientific discovery, reading 1,500 papers and running 42,000 lines of code in a single run, delivering 6 months of research in days with 79% accuracy.

• Google’s AI Tools A New Era for Traders – Google Finance now offers Gemini-powered Deep Search for detailed financial research, plus prediction market data to forecast trends and enhanced earnings tracking.

• Comet Assistant Smarter AI Browsing - Comet upgrades empower users with multitasking AI that handles complex workflows, boosts productivity by 23%, and puts users in control of web actions seamlessly.

• Snap & Perplexity AI Chat Revolution - Snapchat partners with Perplexity in a $400M deal to integrate AI-powered search in chats, launching January 2026 for smarter, seamless in-app answers.

• Parallel Search API AI Web Search - The Parallel Search API simplifies AI web data retrieval, delivering dense, relevant content in one call. It reduces token use, lowers latency, and boosts search accuracy for AI agents.

Paper of The Day

The paper "Large language models replicate and predict human cooperation across experiments in game theory" demonstrates that large language models (LLMs) can effectively simulate human cooperative behavior in classical game-theoretic experiments. Using open-source models like Llama, Mistral, and Qwen, the study shows Llama closely replicates human cooperation patterns, capturing deviations from rational choice theory, while Qwen aligns more with Nash equilibrium predictions. The authors developed a refined prompting and verification process to reliably extract LLM decisions and successfully reproduced human-like behavior without persona-based prompting. Extending beyond original experimental parameters, LLMs generated new, testable hypotheses for unexplored strategic settings. This work illustrates the potential of LLMs as digital twins of human decision-making, providing a scalable, transparent tool for social and behavioral science research that complements traditional game theory by modeling bounded rationality and heuristic-driven human behavior.

To read the whole paper 👉️ here