PLUS: Amazon's historic AI job cuts and Mercor's $10B valuation
Good morning
Qualcomm is stepping into the AI data center arena, unveiling new accelerator chips aimed squarely at Nvidia's market leadership. The move signals a significant shift in the competitive landscape for AI hardware and sent the company's stock soaring.
By targeting the less power-intensive inference market instead of training, Qualcomm is taking a different strategic approach. With a previous attempt to enter this space falling short, the key question is whether the current AI boom provides the opportunity it needs to finally succeed.
In today’s Next in AI:
Qualcomm challenges Nvidia with new AI chips
Amazon’s major AI-driven job cuts
Mercor’s $10B human-in-the-loop valuation
NVIDIA’s new open-source robotics push
The AI Chip War Heats Up
Next in AI: Qualcomm is making a major play for the AI data center market, announcing new accelerator chips designed to compete directly with industry leaders Nvidia and AMD. The move signals a new front in the battle for AI hardware dominance and sent the company's stock soaring.
Decoded:
Qualcomm is strategically targeting AI inference—the process of running models—rather than the more power-intensive training market, promoting lower operational costs and power consumption.
The company plans a phased rollout, starting with the AI200 chip in 2026 and the AI250 in 2027, built by scaling its proven Hexagon mobile NPUs for the massive data center market.
This marks a renewed push into the data center space for Qualcomm, following a previous attempt in 2017 that struggled against incumbents, but the current AI boom creates a far different landscape.
Why It Matters: Qualcomm's entry introduces much-needed competition into a market largely controlled by Nvidia, potentially driving down costs for AI developers. The company's focus on power-efficient inference could become a key advantage as businesses scale AI applications for everyday use.
The $10B Human Touch
Next in AI: AI training startup Mercor raised $350 million in a new funding round, quintupling its valuation to an impressive $10 billion.
Decoded:
Mercor began as an AI-driven hiring platform but pivoted after discovering a more critical need: supplying top AI labs with highly skilled domain experts to train foundation models.
The company’s growth accelerated after Meta’s major investment in competitor Scale AI, which prompted AI labs like OpenAI and Google to cut ties over neutrality concerns.
Today, Mercor manages a network of over 30,000 specialized contractors—including doctors, lawyers, and scientists—who are collectively paid over $1.5 million each day to teach AI agents.
Why It Matters: Mercor's massive valuation highlights a fundamental truth in the AI race: human expertise is the most valuable resource for building capable models. This investment signals that the human-in-the-loop approach is not just a temporary fix but a core, lucrative part of the AI economy.
Amazon's AI Overhaul
Next in AI: Amazon is initiating its largest-ever corporate layoff, potentially cutting up to 30,000 jobs as part of a major AI-driven overhaul. CEO Andy Jassy directly links the move to generative AI reshaping the company’s operational needs and workforce structure.
Decoded:
The cuts will impact nearly 10% of Amazon's 350,000 corporate employees across various divisions, including human resources, devices, and operations.
CEO Andy Jassy explicitly stated that as the company deploys more generative AI and autonomous agents, it will reduce the total corporate workforce over the next few years.
This move follows a broader trend in tech, with companies like Microsoft, Meta, and Salesforce also trimming staff while citing increased AI adoption as a key catalyst for operational changes.
Why It Matters: This is one of the most significant examples of a tech giant directly connecting mass layoffs to its AI strategy, moving the conversation from theory to reality. Professionals should view this as a clear signal that adapting to AI-driven workflows is no longer optional but essential for future career relevance.
NVIDIA Powers Up Robotics
Next in AI: NVIDIA is deepening its commitment to the open-source robotics community with new contributions to the Robot Operating System (ROS) and the release of Isaac ROS 4.0, aiming to accelerate the development of 'Physical AI.'
Decoded:
The new Isaac ROS 4.0 is now available, providing developers with GPU-accelerated libraries and AI models on the powerful NVIDIA Jetson Thor platform.
The company is contributing GPU-aware abstractions directly to ROS 2, enabling the framework to efficiently manage different processors and keep pace with hardware innovation.
To help developers optimize performance, NVIDIA open-sourced the Greenwave Monitor, a tool for quickly identifying bottlenecks and speeding up robot development.
Why It Matters: By directly improving the core ROS framework, NVIDIA ensures its powerful hardware becomes a top choice for the next generation of autonomous machines. This move makes it easier for developers to build and deploy advanced AI in real-world robots.
AI Pulse
Anthropic expanded its alliance with Deloitte, making Claude available to 470,000 employees globally in its largest enterprise AI deployment to date.
AMD partnered with the U.S. Department of Energy on a $1B deal to develop two new AI-focused supercomputers.
OpenAI estimated that hundreds of thousands of its 800 million weekly active users show signs of severe mental health crises, releasing the data alongside updates to improve how ChatGPT handles sensitive conversations.
Australia's sued competition watchdog sued Microsoft, alleging the company misled millions of subscribers by failing to disclose a cheaper, non-Copilot 'Classic' plan when it increased prices for its AI-integrated subscriptions.