đŚžItâs Not Just Nvidia anymore, itâs warâŚ
Plus: How to Master Dynamic Workflows, a new feature by Claude.
Everyone wants to be king, and when you are, competitors will do anything to take your crown. NVIDIAâs crown is highly coveted these days; hyperscalers are doing everything possible to create their own chips to minimize dependence on NVIDIA and make a dent in that market to increase revenue. We list a few surprising companies getting into the chips game. Claude dropped another great feature, and we share a âHow Toâ use it, and AI lawlessness is being challenged. Letâs dive in and, as always, stay curious.
đ° AI News and Trends
AIâs Progressive Challenge: Democrats wonât let AI be loose.
How to Master Dynamic Workflows, a new feature by Claude.
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Itâs Not Just Nvidia anymore, itâs warâŚ
đ Learning Corner - Claudeâs Dynamic Workflows
đ° AI News and Trends
Analysts forecast that lithium demand will increase three- to sixfold in the next decade, but a mining boss in China argued that even these bullish forecasts were underestimates.
Nvidia CEO Jensen Huang is set to join the advisory board of Tsinghua University School of Economics and Management, which counts Tim Cook, Elon Musk, and Mark Zuckerberg among its 65 members.
Anthropic on Thursday announced a new funding round valuing it at $965 billion, surpassing rival OpenAI as the worldâs most valuable AI startup.
Chinese AI company launches â95% accurateâ pet translator
Radical AIâs âself-drivingâ lab designs and tests new alloys, and creates new materials, speeding up a material R&D process that often takes human scientists 20 years or more.
A Google employee allegedly used inside information to win $1.2 million on Polymarket
Apple to Overhaul iOS 27 Siri and lots of AI Features
AIâs Progressive Challenge
A growing group of progressive Democrats is taking a tougher stance on artificial intelligence, creating a widening divide inside the Democratic Party over the future of AI regulation.
Leaders like Bernie Sanders, Alexandria Ocasio-Cortez, and Ro Khanna are pushing back against the rapid expansion of AI infrastructure, particularly large data centers tied to companies like Meta. Their concerns range from environmental damage and water usage to worker displacement and the growing influence of AI money in politics. Sanders has proposed a moratorium on new data centers and renewed calls to eliminate super PAC influence, while AOC has highlighted pollution concerns linked to AI facilities in Georgia.
Khanna, meanwhile, is advocating for a âWork for Americaâ initiative that would retrain up to 1 million Americans for tech and infrastructure jobs as AI automation accelerates. The debate signals that AI policy is quickly becoming one of the most politically divisive issues in Washington, with progressives demanding stricter oversight as the AI industry races to expand.
How to Master Dynamic Workflows
In Claude Code, dynamic workflows allow the agent to move beyond linear chatting by writing and executing its own orchestration scripts. It acts as a âmanager,â spawning multiple parallel sub-agents to tackle complex, multi-part tasks simultaneously.
Dynamic workflows transform Claude Code from a single agent into an orchestrator. Instead of solving a massive problem step-by-step in one thread, Claude breaks the problem down, creates a fleet of sub-agents to handle the sub-tasks in parallel, verifies their output, and merges the results into a final solution. This is best for large-scale refactors, documentation generation, or complex bug hunting across large codebases. Be aware, your tokens may run out quickly if limited, or send you a large bill.
How to Use Dynamic Workflows
Since this is currently in Research Preview, you access it through specific commands in the Claude Code CLI or the supported IDE extensions.
1. Enable/Invoke via CLI
In the Claude Code terminal, you donât usually need a special âmodeâ switch; you simply prompt Claude with a high-level, complex task that implies parallelization.
Example Prompt: âRefactor all export statements in the
/srcdirectory to use named exports instead of default exports, and update all corresponding imports.âObservation: You will see Claude mention that it is âstarting a dynamic workflowâ or âspawning sub-agents.â
2. Scoping the Task (Best Practice)
Because this feature consumes significantly more tokens (as it is running many instances of Claude at once), start small:
Target a specific folder: Instead of âfix the whole repo,â try âfix all type errors in
src/components/.âBe specific about the goal: âGenerate README files for every sub-package in this monorepo.â
3. Monitor Progress
While the workflow is running, the CLI will typically show a progress indicator or a list of active sub-tasks.
Claude will automatically handle âretriesâ if a sub-agent fails.
It will perform a âvalidationâ phase at the end to ensure the parallel work didnât break the codebase.
4. Requirements
Plan: You must be on a Pro, Team, or Enterprise plan.
Tools: Ensure you are using the latest version of the Claude Code CLI (
npm install -g @anthropic-ai/claude-code) or the VS Code extension.
Warning: As mentioned above, in case you dintât read all the way down here, watch your token usage/billing. Since dynamic workflows run hundreds of parallel calls, a single command can consume a large portion of your rate limit or budget much faster than a standard chat session.
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Itâs Not Just Nvidia anymore, itâs warâŚ
The global AI boom has sparked an infrastructure arms race. While Nvidia still commands 80%â90% of the market (briefly hitting a $4 trillion valuation), the worldâs tech giants are tired of waiting in line. Faced with 10-week to 6-month lead times, the industry is shifting toward âVertical AI Infrastructure,â designing custom silicon to bypass the middleman.
The Challenger Bench
Nearly every major âhyperscalerâ now has a custom chip program to lower costs and boost performance:
The Big Three: Google (TPUs), Amazon (Trainium/Inferentia), and Microsoft (Maia) are building in-house to power their massive cloud ecosystems.
Social & Media: Meta is using its MTIA chips for ad targeting, while ByteDance (TikTok) is reportedly developing custom CPUs to escape supply chain bottlenecks.
Specialized Tech: Tesla (Dojo) is focused on autonomous robotics, while Apple continues to dominate on-device AI via its Neural Engine.
The Direct Rivals: AMD (MI300 series) remains Nvidiaâs strongest commercial GPU competitor, while Intel fights for relevance with its Gaudi accelerators.
Why Go Custom?
For these companies, the move isnât just about saving money; itâs about survival. Custom silicon offers:
Optimization: Chips tuned specifically for their own AI models (like Gemini or Llama).
Efficiency: Lower power consumption and faster âinferenceâ (running the AI).
Sovereignty: Protection against global shortages and export restrictions.
From Earth to Mars
The race has even reached deep space. NASA recently tested its High Performance Spaceflight Computing (HPSC) chip. This radiation-hardened processor delivers 100x to 500x the performance of current space-grade tech, allowing future Mars rovers and lunar habitats to navigate autonomously without waiting for instructions from Earth.
Companies understand that creating the models and code is not enough; they must own the sand it runs on.