Hardware

NVIDIA has announced CUDA Rust, a push to make Rust a first-class language for GPU kernels. Two open-source NVlabs projects cover the two CUDA programming models: cuda-oxide compiles SIMT kernels from Rust MIR through Pliron and LLVM to PTX, while cutile-rs JIT-compiles Tile kernels through CUDA Tile IR on stable Rust 1.89+.

Pollen Robotics, the Bordeaux robotics team at Hugging Face, opened pre-orders for Microduck — a 25 cm bipedal robot where every movement is a neural policy trained in MuJoCo and exported to ONNX. At $399, it puts the full sim-to-real loop on a desk: 15 motors, camera, LiDAR, two IMUs, and an Apache-2.0 training stack you can retrain yourself.

Netflix engineers detailed how they handle wide partitions in Apache Cassandra for the TimeSeries Abstraction. Two approaches work together: Time Slice re-partitioning tunes future partitions at the table level, while dynamic partitioning detects and splits oversized partitions per TimeSeries ID on the read path. Detection runs via byte counting and Kafka, splits are checksum-validated, and Bloom filters route reads to parallel child partitions. Average read latency dropped from seconds to low double-digit milliseconds, with 500MB+ partitions staying available.

Zyphra Introduces Tensor and Sequence Parallelism (TSP): A Folded Parallelism Strategy That Reduces Both Parameter and Activation Memory Across the Same GPU Axis

OpenAI is moving from a limited pilot to broad deployment of its Trusted Access for Cyber program, introducing GPT-5.4-Cyber — a variant of GPT-5.4 fine-tuned to be cyber-permissive — for thousands of vetted defenders.

Run Google’s latest omni-capable open models faster on NVIDIA RTX AI PCs, from NVIDIA Jetson Orin Nano, GeForce RTX desktops to the new DGX...

The scaling of inference-time compute has become a primary driver for Large Language Model (LLM) performance, shifting architectural focus toward inference efficiency alongside model...

For the modern AI developer productivity is often tied to a physical location. You likely have a 'Big Rig' at home or the office—a...

While the tech folks obsesses over the latest Llama checkpoints, a much grittier battle is being fought in the basements of data centers. As...

In the high-stakes world of AI infrastructure, the industry has operated under a singular assumption: flexibility is king. We build general-purpose GPUs because AI...

Maia 200 is Microsoft’s new in house AI accelerator designed for inference in Azure datacenters. It targets the cost of token generation for large...

Why treat LLM inference as batched kernels to DRAM when a dataflow compiler can pipe tiles through on-chip FIFOs and stream converters?StreamTensor is a...

What MLPerf Inference Actually Measures? MLPerf Inference quantifies how fast a complete system (hardware + runtime + serving stack) executes fixed, pre-trained models under strict...

Table of contentsHardware Generation without TemplatesInput IR: Affine, Relation-Centric Semantics (Deconstruct)Front End: FU Graph + Memory Co-Design (Architect)Back End: Compile & Optimize to RTL...

NVIDIA has unveiled a major milestone in scalable machine learning: XGBoost 3.0, now able to train gradient-boosted decision tree (GBDT) models from gigabytes up...

Large language models (LLMs) have found applications in diverse industries, automating tasks and enhancing decision-making. However, when applied to specialized domains like chip design,...

Compute Express Link (CXL) emerges as an innovative technological solution addressing critical memory wall challenges in modern computing infrastructures. The interconnect technology presents a...

Supercomputers are the pinnacle of computational technology, which is made to tackle complex problems. These devices manage enormous databases, facilitating advances in sophisticated scientific...

In recent years, there has been significant development in the field of large pre-trained models for learning robot policies. The term "policy representation" here...

LLMWare.ai, a pioneer in deploying and fine-tuning Small Language Models (SLMs) announced today the launching of Model Depot in Hugging Face, one of the...

Cerebras Systems has set a new benchmark in artificial intelligence (AI) with the launch of its groundbreaking AI inference solution. The announcement offers unprecedented...

The demand for processing power and bandwidth has increased exponentially due to the rapid advancements in Large Language Models (LLMs) and Deep Learning. The...

The Sohu AI chip by Etched is a thundering breakthrough, boasting the title of the fastest AI chip to date. Its design is a...

Artificial intelligence algorithms demand powerful processors like GPUs, but acquiring them can be a major hurdle. The high initial investment and maintenance costs often...

In an era where the demand for rapid and efficient AI model processing is skyrocketing, SambaNova Systems has shattered records with the release of...

In artificial intelligence (AI), utilizing monolithic large language models (LLMs) such as GPT-4 has been pivotal in advancing modern generative AI applications. However, the...

The Language Processing Unit (LPU) represents a groundbreaking advancement in processor technology, specifically engineered to optimize tasks associated with natural language processing (NLP). Unlike...

Deep learning has dramatically transformed industries, from healthcare to autonomous driving. However, these advancements wouldn’t be possible without parallel developments in hardware technology. Let's...

Meta, the tech giant behind popular platforms such as Facebook and Instagram, is pushing the boundaries of artificial intelligence (AI) infrastructure by introducing the...

Researchers and developers need to run large language models (LLMs) such as GPT (Generative Pre-trained Transformer) efficiently and quickly. This efficiency heavily depends on...

In the era of AI-driven transformations and soaring computing demands, NVIDIA launches its Blackwell platform, which emerges as a game-changer. Named after the renowned...

Artificial Intelligence (AI) has made significant strides in the past few years with the advancements in Deep Learning (DL) and the advent of Large...

Although large language models (LLMs) have shown impressive capabilities when it comes to language processing, they are computationally expensive and require sophisticated hardware infrastructure....

Researchers from multiple universities have addressed the challenge of designing large-scale DNN chiplet accelerators, focusing on optimizing monetary cost (MC), performance, and energy efficiency....

Google made waves with the launch of its tensor processing unit, Cloud TPU v5p, accompanied by the groundbreaking supercomputer architecture known as AI Hypercomputer....

Amidst persistent industry rumors, Microsoft's long-anticipated revelation came to light during the Ignite conference, marking a pivotal moment in the tech landscape. The tech...

In robotics, researchers face challenges in using reinforcement learning (RL) to teach robots new skills, as these skills can be sensitive to changes in...

In a world where the demand for data-centric local intelligence is on the rise, the challenge of enabling devices to analyze data at the...

In the ever-evolving landscape of artificial intelligence, the need for faster and more efficient processing capabilities has been a persistent challenge for computer scientists...

Researchers from Seoul National University address a fundamental challenge in robotics - the efficient and adaptable control of robots in dynamic environments. Traditional robotics...

Neuromorphic computing is inspired by the human brain's structure and function. A neuromorphic chip is a device that uses physical artificial neurons to do...

In the fast-paced world of Artificial Intelligence (AI) and Machine Learning, staying updated with the latest trends, breakthroughs, and discussions is crucial. Reddit, the...

The ongoing AI revolution, set to reshape lifestyles and workplaces, has seen deep neural networks (DNNs) play a pivotal role, notably with the emergence...

The release of Meta's new open-source Llama 2 has sparked discussions about large language models (LLMs) use cases. However, accessing and running Llama 2...

A data warehouse is a data management system for data reporting, analysis, and storage. It is an enterprise data warehouse and is part of...

Artificial Intelligence has limitless possibilities, which is truly evident from the new releases and developments it introduces everyone to. With the release of the...

A Field Programmable Gate Array (FPGA) is an integrated circuit that can be configured and customized after manufacturing. These chips are called "field-programmable" because...

At the ISC23 keynote, Intel announced Aurora genAI – a science-focused generative AI model with a trillion parameters, almost six times more than in...

Multiple Natural Language Processing (NLP) tasks have been completed using a large-scale transformers architecture with state-of-the-art outcomes. Large-scale models are typically pre-trained on generic...

Machine learning (ML) models are still developing in challenging ways, both in terms of size and technique. Large language models (LLMs) serve as instances...

Artificial Intelligence is making some remarkable progress in almost every domain possible. With the increasing popularity and advancements, AI is transforming how we work...

Future economic growth could be significantly impacted by AI chips, which will unavoidably be used in robotics, smart homes where electronic items are becoming...

Artificial Intelligence has been the talk of the town ever since it was introduced. It has contributed to almost every single domain with its...

Companies that design, develop, and produce FPGAs  (Field-Programmable Gate Arrays) are known as FPGA (Field-Programmable Gate Array) companies. FPGAs are a class of programmable...

McKinsey has recently reported that Machine Learning applications have seen a skyrocketing rise of $165 billion yearly. But any Machine Learning model must be...

Due to recent technological breakthroughs, the number of always-on or ambient smart gadgets has proliferated in recent years. However, such technical developments also prompt...

Academic researchers' work over ten years ago was crucial in developing contemporary artificial intelligence as we see it today. It was demonstrated that training...

What is an AI Accelerator? Machine Learning(ML), particularly its subfield, Deep Learning, mainly consists of numerous calculations involving Linear Algebra like Matrix Multiplication and Vector...

Open-source hardware and software have been indispensable to growing industries' demand to scale innovations, especially in AI. Almost every industry is adopting AI in...

Information is processed by microprocessors in computers, data centers, and smartphones by manipulating electrons that pass through solid semiconductors. However, our brains have a...

Renesas Electronics Corporation offers complete semiconductor solutions enabling billions of connected, intelligent devices to improve people's work and life. These solutions are based on...

Conventional computing architectures severely constrain artificial intelligence's ability to improve technology. In traditional models, memory storage and computing occur in separate areas of the...

Electronic design automation (EDA), often known as computer-aided design (CAD), is a class of software tools used to create electronic systems like integrated circuits...

Products for the "edge" market include drones, internet of things devices, and phones. And This market is served by the very broad field of...

Gigantic models are those models that have to be trained using billions or trillions of parameters. Due to significant communication overheads, current general purpose...

As we walk into the age of AI, there is an exponential rise in the demand for GPU. The not-so-old method of parallel computing...

The first hyper-converged system with complete VMware Cloud Foundation SDDC Manager integration is VxRail. Host and implement both old-school and new-school applications are on...

A multidisciplinary research team has created a device that consumes a fraction of the energy needed by current general-purpose AI computing platforms to run...

LAN is the network that connects client computers to servers, a piece of information we are all aware of, but what most people aren’t...

The ability to identify non-trivial patterns in data using computational methods has sparked the creation of sophisticated machine intelligence systems with a wide range...

When it comes to powerful chips, the US company Cerebras has you covered. They have trained their AI model on a single device powered...

To perform difficult industrial and domestic tasks, robots must be able to model and manipulate elastoplastic items (e.g., stuffing dumplings, rolling sushi, and making...

Semiconductors are employed in almost every industry and have become a valuable asset. The development and production of these chips is a complex task....

This Article is written as a summay by Marktechpost Staff based on the research article 'Reconfigurable heterogeneous integration using stackable chips with embedded artificial...

This Article is written as a summay by Marktechpost Staff based on the paper 'An on-chip photonic deep neural network for image classification'. All...

This Article Is Based On The NVIDIA Article 'NVIDIA Releases Open-Source GPU Kernel Modules'. All Credit For This Research Goes To The Researchers of...

This Article Is Based On The PR Article 'GrAI Matter Labs Unveils Life-Ready AI with GrAI VIP at GLOBAL INDUSTRIE'. All Credit For This...

Please Don't Forget To Join Our ML Subreddit Google introduces the preview of its latest machine-learning clusters at its I/O conference, aiming for nine exaflops...

This Article Is Based On The Research Article 'Habana® Labs Launches Second-generation AI Deep Learning Processors'. All Credit For This Research Goes To Intel...

Please don't forget to join our ML Subreddit Need help in creating ML Research content for your lab/startup? Talk to us [email protected] Deep learning has emerged...

We have a plethora of AI models being developed by numerous businesses. But these require a lot of time and resources. Because high-performance AI...

The creation of application-specific hardware accelerators has resulted from the advent of ML-based approaches in solving diverse challenges in vision and language. Standard approaches...

Since the inception of modern machine learning, the goal has been to make workloads that use the technology as efficient as feasible. Considering the...

If data is the fuel for Artificial Intelligence (AI), the computation is the engine. The ever-increasing computational requirements of modern AI systems have prompted...

Graphcore, a U.K.-based AI computer company, improved the performance of its computers without changing anything about their specialized AI processor cores. TSMC's wafer-on-wafer 3D...

Qualcomm, one of the world's leading 5G inventors, has introduced its newest modem technology, codenamed Snapdragon X70 at Mobile World Congress in Barcelona, Spain....

Artificial intelligence may never be able to take the place of the human brain. The fact that the human brain adjusts when it learns...

Human conversation is dynamic, with many exceptions and unexpected ways to express oneself. In recent years, significant progress has been made to help machine...

On a silicon sheet, the most modern processors resemble expansive suburbs, with transistors stacked like blocks of dwellings. IBM attempts to flatten the entire...

A prominent challenge physicist and computer scientist faces is developing ways to accurately rebuild spatial fields from data gathered by sparse sensors. This process...

The Chinese e-commerce giant Alibaba launched a new server chip, Yitian 710, which it hopes will help boost its cloud computing business and compete against...

Every day, people make countless decisions based on their understanding of their surroundings as a continuous sequence of events. Artificial intelligence systems that can...

Transformer-based language models have made rapid progress in many natural language processing (NLP) applications, thanks to the availability of large datasets, large computation at...

In today’s world, it’s critical to develop systems that can understand 3D data about the world. For example, autonomous automobiles require 3D understanding to...

Matrix multiplication is one of the essential operations in machine learning (ML). However, these operations are extensively computationally costly due to the extensive use...

DNA contains the genetic information that influences everything from eye color to illness and disorder susceptibility. Genes, which are around 20,000 pieces of DNA...

Federated learning is a machine learning environment in which multiple clients (such as mobile devices or entire enterprises, depending on the task at hand)...

In 2018, Intel launched its first-generation Loihi chip, which was created using a proven 14nm process node and integrated 128k Neurons at the same...

Every bit of data that goes over the internet, from paragraphs in an email to 3D images in a virtual reality environment, is susceptible...

Artificial intelligence (AI) has transformed industries all over the world, including the healthcare sector. From fitness bracelets to glucose monitoring, modern technology allows anyone...