AMD just previewed its next-gen Radeon RX 9070 and 9070 XT GPUs at CES, built on a new 4nm RDNA 4 architecture. The biggest shift is FSR 4, which now relies on machine learning upscaling powered by dedicated on-die AI accelerators. Both cards drop in Q1, though specs and prices remain under wraps.
xAI just closed a massive $6 billion Series C funding round, pushing its valuation to $45 billion. Backed by Nvidia, AMD, and Sequoia, the fresh cash will help double its 100,000-GPU supercluster and accelerate the rollout of its next-generation Grok models.
Microsoft AI CEO Mustafa Suleyman just pushed back against claims that AGI is achievable on current hardware like Nvidia GB200s, estimating it will take two to five more chip generations—or five to ten years. He also distanced practical AGI from sci-fi superintelligence, arguing builders should focus on useful, accountable AI companions instead of chasing the singularity.
NVIDIA Research and the University of Maryland just introduced QUEEN, an AI model that enables streaming free-viewpoint 3D video. By reusing renders of static regions and focusing on dynamic content, it renders at roughly 350 frames per second on Tensor Core GPUs. Why it matters: It makes real-time, multi-angle streaming feasible for live sports, virtual meetings, and robot teleoperation.
OpenAI CEO Sam Altman just predicted that 2025 could bring the first real AGI systems capable of solving complex tasks with multiple tools. While the initial arrival might feel quiet, Altman warned that the eventual impact of superintelligence and resulting job displacement will be far more intense than people think.
Amazon is teaming up with Anthropic to build Project Rainer, a massive AI supercomputer powered by hundreds of thousands of its custom Trainium 2 chips. AWS says the system is 30% to 40% cheaper than Nvidia setups and five times larger than Anthropic’s current training cluster. Why it matters: Amazon is proving Nvidia isn't the only viable game in town, giving frontier AI builders a much cheaper route to compute.
Nvidia just debuted Fugatto, a generative audio model that transforms existing sounds and invents entirely new soundscapes from text prompts. It can morph piano chords into singing voices or turn a train rumble into an orchestra. Nvidia is withholding its public release for now over safety and copyright concerns.
Nvidia just confirmed its flagship Blackwell AI chips are in full production, brushing off recent server cooling rumors. The company has already shipped 13,000 samples to customers this quarter, with CEO Jensen Huang assuring investors that systems are standing up in great shape. Why it matters: Demand remains voracious, and Nvidia's AI data center revenue engine is showing zero signs of cooling down.
Nvidia just launched two new NIM microservices for its Earth-2 digital twin platform at SC24. CorrDiff delivers kilometer-scale weather resolution 500x faster than traditional CPU models, while FourCastNet generates two-week global forecasts 5,000x faster. It gives meteorologists and insurers practical tools to spot extreme weather before disaster strikes.
ESPN just revealed FACTS, an AI-generated avatar being tested to complement hosts on its college football show SEC Nation. Powered by Nvidia’s ACE, Azure OpenAI, and ElevenLabs, the bot pulls from ESPN Analytics to make complex sports metrics accessible. ESPN insists it is definitely not built to replace human talent.
NVIDIA, the Weizmann Institute, and Pheno.AI just unveiled GluFormer, a transformer-based generative AI model that forecasts glucose levels and health outcomes up to four years in advance. Trained on continuous glucose monitor data, it can also predict how a body reacts to specific foods, opening the door to precision preventive care for diabetes.
NVIDIA just released a major suite of robotics development tools at CoRL, headlined by the open-source launch of Isaac Lab 1.2 and six new Project GR00T workflows for humanoids. The company also open-sourced its Cosmos visual tokenizer, running up to 12x faster to accelerate world model training. Why it matters: NVIDIA is actively trying to cement its compute and software stack as the unavoidable operating backbone for the next generation of physical AI.
NVIDIA just launched a new AI Blueprint for video search and summarization, enabling developers to build visual AI agents that analyze massive video archives and live streams using natural language prompts. Powered by vision-language models, the workflow cuts months off deployment for smart cities, warehouses, and traffic management.
Nvidia just released the NVLM 1.0 family of multimodal models, making weights public for its 72B flagship NVLM-D-72B. The model matches frontier proprietary systems like GPT-4o across vision tasks and unexpectedly gained 4.3 points in text benchmarks post-multimodal training, giving open-source developers frontier-grade power.
Runway just launched The Hundred Film Fund to support creative professionals with AI-augmented projects. Grants range from $5K to over $1M alongside $2M in Runway credits, with advisors from Tribeca and NVIDIA backing the effort to keep storytelling artist-led.
NVIDIA just teamed up with the U.S. government and companies like OpenAI and Google on the Partnership for Global Inclusivity on AI. The effort aims to expand access to AI tools in developing nations, with NVIDIA pledging roughly $10 million in free training alongside GPU credits. Why it matters: Frontier AI has been heavily concentrated in wealthy regions, and this effort could help developers in emerging markets build local solutions.
Nvidia just launched AI Aerial, a computing suite for designing, simulating, and running AI radio access networks (AI-RAN). It allows telecom providers to optimize 5G and 6G networks while hosting edge generative AI workloads on the exact same infrastructure. Nvidia is also teaming up with T-Mobile, Ericsson, and Nokia to fast-track commercial adoption.
T-Mobile just teamed up with OpenAI to build IntentCX, a customer service platform powered by OpenAI's APIs and the new o1 model. Slated for rollout next year, the system parses support call transcripts to pinpoint customer pain points, aiming well beyond conventional chatbots.
ByteDance is reportedly teaming up with TSMC to design two custom AI chips for training and inference, targeting mass production by 2026. The effort looks to bypass costly Nvidia GPUs and navigate tightening U.S. export controls. Why it matters: Going in-house could save billions, though the plans remain in early stages and subject to regulatory shifts.
Magic just announced LTM-2-mini, an ultra-long context model capable of processing 100M tokens—equivalent to roughly 10 million lines of code or 750 novels. The startup claims its sequence-dimension algorithm is 1,000x cheaper per decoded token than Llama 3.1 405B at that context scale, and revealed $320M in new funding alongside a Google Cloud partnership to build supercomputers.
