Best of NVIDIA — April 2026

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    Article
    Avatar of wheresyouredWhere's Your Ed At·5w

    Four Horsemen of the AIpocalypse

    Ed Zitron argues the AI industry is in a dangerous bubble, presenting four major warning signs: Anthropic's chronic service outages and degraded model quality (Claude Opus 4.7 reportedly worse than 4.6), the revelation that Claude Mythos was held back due to capacity constraints rather than safety concerns, NVIDIA selling more GPUs than can physically be installed with only 15.2GW of data center capacity actually under construction through 2028, and AI inference costs spiraling out of control — with some companies spending up to 10% of headcount costs on LLM tokens. Microsoft is moving GitHub Copilot to token-based billing after costs nearly doubled week-over-week, and Anthropic has already shifted enterprise customers to per-token API rates. Zitron contends that AI revenues are massively overstated through fraudulent ARR accounting, that both Anthropic and OpenAI are burning billions while providing subsidized, unreliable services, and that the entire industry's survival depends on infinite venture capital rather than genuine economic value.

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    Article
    Avatar of nvidiadevNVIDIA Developer·6w

    MiniMax M2.7 Advances Scalable Agentic Workflows on NVIDIA Platforms for Complex AI Applications

    MiniMax M2.7 is a sparse Mixture-of-Experts (MoE) language model with 230B total parameters and only 10B active per token, featuring a 200K context window. NVIDIA details how to deploy it using vLLM and SGLang with specific inference optimizations — a fused QK RMS Norm kernel and FP8 MoE kernel — that deliver up to 2.7x throughput improvements on NVIDIA Blackwell Ultra GPUs. The post also covers building long-running agents via NVIDIA NemoClaw and OpenShell, fine-tuning with the NeMo AutoModel library and NeMo RL, and accessing the model through NVIDIA NIM microservices or free endpoints on build.nvidia.com.

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    Video
    Avatar of tiffintechTiff In Tech·7w

    The Robot Problem Nobody Is Talking About

    A firsthand look at NVIDIA's robotics ecosystem from GTC 2026, covering the Jetson Thor compute module, the sim-to-real gap in robot training, and the emerging data flywheel concept borrowed from autonomous vehicles. Includes interviews with NVIDIA's robotics software lead Spencer Huang on world models and CI/CD for robots, and Open Mind founder Jan Liphardt on OM1, an open-source robot OS with an app store. Also covers a ride in a self-driving Mercedes running NVIDIA's drive stack at L2++, with plans for Level 4 robotaxi deployment via an Uber partnership. Key insight: the tools (Isaac, Groot, Cosmos, OM1) are now open and accessible enough that domain experts without robotics PhDs can start building.

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    Article
    Avatar of tnwThe Next Web·4w

    AI stocks vs dot-com bubble: CAPE at 38, concentration above 2000 levels, but companies are actually profitable

    The Shiller CAPE ratio sits at 38-40, second only to the dot-com peak of 44.19, and S&P 500 top-10 concentration now exceeds year-2000 levels by nearly 50%. However, unlike dot-com era companies, today's AI leaders are massively profitable — Nvidia alone earned $120B in net income, and the tech sector trades at 30x forward earnings versus 50x in 2000. The central unresolved question is whether $660-690 billion in annual hyperscaler capex will generate returns that justify the investment. Bulls point to real earnings growth (Nasdaq-100 up 19% YoY) and committed cloud revenue backlogs; bears highlight OpenAI's $852B valuation with no profits, retail euphoria, and the historical precedent of fibre-optic companies that built real infrastructure but went bankrupt anyway. The bubble question cannot be answered until the AI infrastructure cycle produces results.

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    Article
    Avatar of tnwThe Next Web·5w

    NVIDIA didn’t invest in Xanadu, but it made its CEO a billionaire anyway

    Xanadu Quantum Technologies CEO Christian Weedbrook became a billionaire after the company's stock surged nearly fivefold in six trading sessions, driven entirely by NVIDIA's announcements — not any direct investment in Xanadu. NVIDIA launched Ising, a family of open-source AI models for quantum error correction and calibration, and NVQLink, an architecture connecting GPUs to quantum processing units. These moves validated quantum computing as a near-term engineering problem, triggering a sector-wide rally. Xanadu, the only publicly traded pure-play photonic quantum company, was the biggest beneficiary despite having just $4.6M in 2025 revenue against a market cap that briefly exceeded $3 billion. The piece examines the extreme valuation multiples across quantum stocks — Rigetti at 1,025x sales, D-Wave at 325x — and questions whether the market's timeline matches the technology's actual trajectory. The broader theme is NVIDIA's ability to reshape entire sectors through strategic positioning, ensuring it sits at the center of quantum computing if and when it matures.

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