AI chip startup NeuReality introduces its NR1-P object-oriented hardware architecture
NeuReality targets deep learning inference workloads on the edge, aiming to reduce CAPEX and OPEX for infrastructure owners
Read More →AI chips in the real world: Interoperability, constraints, cost, energy efficiency, and models
The answer to the question of how to make the best of AI hardware may not be solely, or even primarily, related to hardware
Read More →Trailblaizing end-to-end AI application development for the edge: Blaize releases AI Studio
You might not know it by reading this news, but Blaize is an AI chip company. Blaize is now boldly going where none of its ilk has gone before, releasing a software development product. And that's not the only reason AI Studio is interesting
Read More →Nvidia’s acquisition of Arm strengthens its ecosystem, brings economies of scale to the cloud, expansion to the edge
Nvidia is after a double bottom line in the AI chip market: Better performance and better economics. Arm's acquisition helps with the economies of scale in the data center and expands Nvidia's footprint to the edge
Read More →AI chips in 2020: Nvidia and the challengers
Now that the dust from Nvidia's unveiling of its new Ampere AI chip has settled, let's take a look at the AI chip market behind the scenes and away from the spotlight
Read More →Deep Learning Software vs. Hardware: NVIDIA releases TensorRT 7 inference software, Intel acquires Habana Labs
NVIDIA's software library latest release brings significant performance improvements, which NVIDIA says enable conversational AI. But Intel is stepping up its game too, by acquiring Habana Labs, an AI chip startup that promises top performance on the hardware level.
Read More →NVIDIA GPUs now work with Arm processors, Magnum open source I/O accelerates data workloads for AI
NVIDIA expands its ecosystem, flexes its software muscle, and takes a bet on new processors, workloads, and use cases. The developments paint a new picture in the AI chip race in the cloud and the edge.
Read More →Nvidia Rapids cuGraph: Making graph analysis ubiquitous
A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs.
Read More →Run:AI takes your AI and runs it, on the super-fast software stack of the future
Startup Run:AI exits stealth, promises a software layer to abstract over many AI chips
Read More →Nvidia GPUs for data science, analytics, and distributed machine learning using Python with Dask
Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.
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