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NVIDIA Launches NIM, Telstra + Accenture, Halliday AI glasses, New Google LLM architecture
NEW LAUNCHES
The latest features, products & partnerships in AI
Google’s new LLM architecture cuts costs with memory separation
Google Chrome is testing a new AI feature that combats annoying pop-up ads
Microsoft and Pearson are launching an AI upskilling initiative
The Halliday AI smart glasses might be the most innovative wearable yet
Adobe, General Assembly announce AI skills program to train millions in India
AI AGENTS
Launches, research & more from the AI Agent Report Newsletter
AI INFRASTRUCTURE
Buildout, financing, policy & chips
Transforming into AI factories the rise of decision-making engines in modern data centers
Microsoft launches CoreAI division to accelerate AI infrastructure development and integration
New AI chip export restrictions to be based on 3-tier system — here’s how it works
Insatiable demand for AI services is fueling a new industry of custom chips
Biden unveils AI policies to combat foreign risks for data centers and connected cars
IMPLEMENTATION
Announcements, strategies & case studies
IN OTHER NEWS
Compelling stories beyond the usual categories
Stanford HAI’s global training initiatives educate policymakers on AI governance
FTC refers Snapchat AI chatbot complaint to Justice Department
The new wave of AI banking apps helping consumers manage their finances
AI-powered websites are impersonating major sports news outlets
While writers are anxious about AI, readers don’t seem to care much
Most people are unaware they’re already using AI, Gallup survey finds
AI VIDEO
Luma Labs has launched Ray 2, an AI video generation tool that creates realistic 10-second clips from text descriptions, powered by 10x more computational resources than its previous version. The platform offers both free 720p and premium 1080p tiers at $66.49 monthly, while competing with other players like OpenAI's Sora through its focus on streamlined operation and quick generation times. The company is driving adoption through a $7,000 rewards program, with future plans to add features like image-to-video conversion and advanced editing tools.
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What’s happening in AI right now
AI hardware wars
A battle is unfolding over who will control the foundational infrastructure powering artificial intelligence. This week brought major developments that highlight how tech giants and governments are jockeying for position in compute, chips, and data centers - the essential building blocks enabling AI advancement.
Microsoft's infrastructure power play
Microsoft launched a new division called CoreAI, aiming to accelerate AI infrastructure development across its software ecosystem. Led by Jay Parikh, the initiative combines expertise from Microsoft's Developer Division, AI Platform, and Office of the CTO teams. The goal is ambitious but focused: integrate autonomous AI agents into all software categories by 2025 using Azure's cloud platform as the foundation.
The custom silicon rush
The insatiable appetite for AI compute is driving unprecedented demand for custom semiconductor solutions. Industry projections suggest custom silicon will represent 25% of AI accelerators by 2028. This shift is forcing data centers to operate more like manufacturing plants focused on operational efficiency. The semiconductor industry is adapting its business model accordingly, with new specializations emerging in chip design, manufacturing, and IP development.
Data centers transform into AI factories
Traditional data centers are evolving into what some call "AI factories" - massive compute facilities purpose-built for AI workloads. This transformation brings industrial-scale challenges in power management, reliability, and environmental impact. Energy consumption in these facilities is projected to triple by 2030, making sustainable power solutions critical.
Government steps into the game
The White House made several strategic moves this week to strengthen America's AI infrastructure position. New executive orders will allow AI data centers on federal lands (with clean energy requirements), ban connected vehicle tech from China and Russia starting 2027, and implement enhanced cybersecurity measures for critical infrastructure.
Edge computing paradox
Interestingly, recent research from Hong Kong University and Microsoft reveals that AI edge computing is actually increasing cloud usage rather than replacing it. The study highlights the effectiveness of hybrid approaches, suggesting future AI infrastructure may rely on sophisticated orchestration between edge and cloud resources rather than favoring one over the other.
Looking ahead
These developments paint a clear picture: the next phase of AI competition will be won or lost based on infrastructure capabilities. Success will require mastering custom silicon development and deployment, sustainable power management at massive scale, hybrid edge-cloud architectures, and government partnerships and compliance.
The companies and countries that can build and control these foundational elements will shape AI's trajectory. What remains to be seen is whether this infrastructure arms race will concentrate AI power in the hands of a few giants or if new players can carve out meaningful positions.
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AI generated art
A look at the art and projects being created with AI
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