In partnership with
NEW LAUNCHES
The latest features, products & partnerships in AI
IMPLEMENTATION
Announcements, strategies & case studies
AI MODELS
Deployment, research, training & infrastructure
IN OTHER NEWS
Compelling stories beyond the usual categories
AI tools we are using
The best way to get AI literate? Try the tools
Why we made Zeni our AI CFO
The AI discourse swings wildly between extremes. Uninformed critics dismiss generative AI as a novelty for producing low-quality outputs, while doomsayers warn that truly innovative AI will disempower humans. What's often lost in this noise are the practical tools that simply make our lives easier. That's why we get excited when we find AI products that deliver real value -- tools that make us more capable, not just more automated.
We didn't just test Zeni, we decided to become customers ourselves. Try Zeni yourself. And as a special offer, Zeni was kind enough to offer CO/AI's paid subscribers a full 20% off their first year
What’s happening in AI right now
The great AI partnership scramble
Infrastructure is the new oilÂ
Amazon doubled down on its Anthropic investment this week with an additional $4 billion, bringing its total stake to $8 billion. The deal makes AWS Anthropic's primary training partner and gives Amazon preferred access to Anthropic's models. But more importantly, it commits Anthropic to using Amazon's custom AI chips - Trainium and Inferentia - for model development.
This focus on AI infrastructure isn't unique to Amazon. NVIDIA just announced major integrations with Microsoft Azure, including new AI-optimized virtual machines built on NVIDIA's Blackwell architecture. KPMG secured a $100 million commitment with Google Cloud aimed at expanding their AI capabilities. MongoDB deepened its Microsoft partnership through Azure OpenAI integrations.
The pattern is clear: control of the underlying infrastructure - chips, cloud computing, training capacity - has become the key strategic advantage in AI. The computing demands of training and running modern AI models are so intense that access to specialized hardware and massive data centers is as crucial as the AI technology itself.
The enterprise scramble
One level down from the infrastructure plays, enterprise tech companies are rushing to pick sides. MongoDB chose Microsoft's Azure platform. Snowflake partnered with Anthropic to integrate Claude 3.5 into its Cortex AI platform. Even government contractors are pairing up - Adtran and Dell announced a partnership to provide AI networking solutions for federal agencies.
These alliances aren't just about technology access. They're about survival in an increasingly consolidated market. Enterprise companies need both the technical resources to develop AI products and the distribution channels to reach customers. The major cloud providers offer both.
The deals also reveal how AI is reshaping traditional business relationships. KPMG isn't just using Google Cloud - they're establishing a Google Cloud Center of Excellence and aiming for $1 billion in incremental growth through AI-powered solutions. This goes well beyond typical vendor partnerships into strategic alignment.
Government attention grows
While tech companies race to build, regulators are starting to push back. The Department of Justice moved to block Google's attempted $2 billion partnership with Anthropic, citing concerns about control over consumer search information. This suggests increased scrutiny of big tech's AI investments and could slow further consolidation.
At the same time, the government is actively seeking AI solutions. The Adtran-Dell partnership specifically targets federal agencies, combining Adtran's networking expertise with Dell's AI infrastructure. This dual role - both regulator and customer - could shape how AI development proceeds.
Creative growth strategies
Not every company can play the infrastructure game. Smaller players are finding creative ways to compete. Perplexity, an AI search tool, is offering free annual Pro subscriptions through partnerships with Xfinity and universities. This growth strategy mirrors early platform companies that used free services to build network effects before monetizing.
Early signs suggest the infrastructure advantages are real. Amazon reports its AI business is growing three times faster than AWS overall, with triple-digit percentage growth. But the industry remains young, and today's apparent advantages could shift as technology evolves.
The next few quarters will be crucial as these partnerships mature and their impact on product development and market share becomes clear. For now, the race to control AI infrastructure continues to accelerate, with billions of dollars being bet on the outcome.
We publish daily research, playbooks, and deep industry data breakdowns. Learn More Here
In Bagel’s most recent article, they reveal how large language models are evolving from prediction tools to cognitive agents. From breaking down math problems to understanding everyday logic, this is AI's next frontier.
Key takeaways:
Training-time methods: These approaches, including fine-tuning and curriculum learning, focus on enhancing AI during development by tailoring its abilities to solve complex tasks and building specialized skills for specific problem areas.
Inference-time methods: Techniques like chain of thought and self-consistency optimize AI’s reasoning and decision-making in real time, enabling more accurate and dynamic problem-solving without requiring retraining.
In other words, Bagel’s article explains how AI is evolving from simple prediction tools to smarter systems that can reason through problems and make better decisions in real time.
📬 Join 30,000+ readers exploring the cutting edge of AI research. Read Bagel’s most recent article to understand how reasoning will define the next leap in AI’s evolution.
AI generated art
A look at the art and projects being created with AI.
