Noticias
Titulares de las redacciones y blogs que seguimos.
4907
Anthropic launches roadshow for proposed initial public offering
Today Anthropic, PBC launched the roadshow for its proposed initial public offering of its Class A common stock.
What could China get from Jensen Huang?
It's difficult to overstate Nvidia's power in today's AI landscape. The company's chips are the bedrock upon which advanced AI technology in the US is…
Here’s what Trump said he knew about Jensen Huang
President Trump held a White House press briefing earlier today and responded to several questions about his knowledge of Nvidia CEO Jensen Huang's affair with…
Comparing the 5090 to the 4090 and B200: How Does It Stack Up?
Benchmark Qwen2.5-Coder-7B-Instruct across NVIDIA's B200, RTX 5090, and 4090 to identify optimal GPUs for LLM inference, compare token throughput, cost.
Build container images on your Runpod Pod with Runpod Weld
Runpod Weld builds and pushes container images from inside a Runpod Pod, no Docker daemon needed. Build a demo image, push it, and run it on a Pod.
How to get started with Qwen3.8-Flash-Next on Runpod Serverless
Deploy Qwen3.8-Flash-Next on Runpod with vLLM's dedicated image. Validated flags, 4x H200 hardware math, measured cold starts, and the NCCL fix you need on day one.
Run DeepSeek R1 on Just 480GB of VRAM
DeepSeek R1 remains one of the top open-source models. This post shows how to run it efficiently on just 480GB of VRAM without sacrificing performance.
Deploying Kimi K3 in 4-bit on a single 8xB300 Pod on Runpod
How to get up and running with Kimi K3 without the overhead of running an entire cluster.
Introducing A40 GPUs for Machine Learning | Runpod
NVIDIA A40 GPUs on Runpod pair high performance with low cost and strong availability, making them a good value for fine-tuning LLMs and machine learning.
NVIDIA A40 and A6000 for Budget LLM Fine-Tuning
Discover why NVIDIA's A40 and A6000 GPUs are the best-kept secret for budget-conscious LLM fine-tuning. With 48GB VRAM, strong availability, and low cost.
How a Solo Dev Built an AI for Dads, No GPU, No Team, Just $5
No GPU. No team. Just $5. This is how one solo developer used Runpod Serverless to build and deploy a working AI product, "AI for Dads", without writing.
Jensen Huang reportedly engaged a PR firm with a history of handling high-profile sex scandals a year ago
The PR firm was enlisted shortly after an Oct. 2025 New York Times report described Alice Huang's business dealings with Jensen Huang, Wired reported.
Everything we know so far about the Nvidia spy scandal targeting CEO Jensen Huang
The leather-jacketed CEO of Nvidia, Jensen Huang, has acknowledged an affair with Megaspeed exec Alice Huang, spurring an investigation by his company and intense discussions…
A short seller flagged Nvidia CEO’s ties to a suspected Chinese spy six months before the scandal
Six months before Nvidia's spy scandal erupted, Culper Research was already questioning Jensen Huang's unusually close relationship with a Chinese executive.
The race is on to sue Nvidia
Nvidia’s stock slid more than 4% after its board opened an investigation into Jensen Huang’s relationship with a suspected Chinese spy, and one securities law…
Announcing Long-Context Training on TPUs with MaxText Context Parallelism
Google Cloud's MaxText framework now supports long-context training up to 14 million tokens on Cloud TPUs by implementing four context-parallel strategies: All-gather, A2A, P2P, and USP. Powered by the Tokamax Splash Attention kernel, these strategies effectively manage attention compute and memory bottlenecks without materializing full key-value sequences in high-bandwidth memory. Developers can adopt these capabilities in MaxText v0.2.4 to achieve…
The global pledge to use AI for climate good is a cruel joke
At this point, reading through the latest splashy pledge to use AI for the good of the environment feels like downing a nonalcoholic beer. Admittedly…
Single-shot and agentic retrieval with Amazon Bedrock Managed Knowledge Base
Amazon Bedrock Managed Knowledge Base now supports single-shot RAG and retrieval-only requests through AgenticRetrieveStream, alongside agentic retrieval. This post explains how the maxAgentIteration parameter matches retrieval effort to each request, using an illustrative internal banking policy assistant.