"We are pleased to partner with Blaize to provide our customers with a cost-effective AI inspection service. Our solution helps our customer reduces up to 85% of the operators' workload and significantly improves product quality," said Colby Chou, IoT BU Head of Accton. The Accton product, Pallas uses Blaize's P1600 SoM, leveraging the programmability and efficiency benefits of the Blaize Graph Streaming Processor (GSP) architecture. The SoM is ideal for rugged and challenging environments and offers the processing power, low latency and energy efficiency crucial for AI inferencing workloads at the edge and the inherent stringent inspection requirements. Accton will be able to implement computer vision applications and new AI inferencing solutions across a range of edge smart vision use cases using the Blaize architecture.

NEXTY is now a Blaize distribution partner serving automotive and industrial markets for AI edge computing in Japan. NEXTY Electronics is a world leader in car electronics, and successfully application of technology and innovation advances in areas such as autonomous driving to other markets, such as IoT, manufacturing and industrial equipment. As such, NEXTY is an ideal distribution partner for Blaize AI hardware and software products serving customers who are adopting AI to process the growing volume of edge data, provide more insight, develop new AI models and deploy new edge systems. "We are pleased to leverage our partnership with Blaize to provide cutting-edge solutions to a wide range of Nexty Electlonics' customers." said Kiyotaka Nakao, Managing Director of Nexty Electlonics. "Edge AI computing technology is evolving rapidly and is sure to become more and more important to the semiconductor industry's business. We hope that combining Nexty Electronics' abundant knowledge of semiconductor peripheral technology with Blaize products and will open up many business opportunities."

All the sessions from Transform 2021 are available on-demand now. Blaize, a company developing AI edge computing platforms for automotive, enterprise, and computer vision markets, today announced that it raised $71 million in series D funding led by Franklin Templeton and Temasek, with participation from Denso and other new and existing backers. The company says that the funds will be used to support its go-to-market and R&D efforts. The pandemic has accelerated the adoption of edge computing, or computation and data storage that's located close to where it's needed. According to the Linux Foundation's State of the Edge report, digital health care, manufacturing, and retail businesses are particularly likely to expand their use of edge computing by 2028.

Until now, most processor chips used for AI applications have been adaptations of devices, like GPUs, that were initially developed for other purposes. This is partly because those existing devices have proven effective enough to be useful, and partly because most companies have seen development of AI-specific processors as prohibitively costly, complex, and/or risky. But, with the AI market poised for intense expansion, diverse new applications at the edge and in endpoints will require silicon that's more closely tailored for specific tasks and situations, removing the need to go to the cloud for AI processing. We are now starting to see indications of how the semiconductor sector is evolving to meet those needs, and what it will mean for the evolution of the AI marketplace and those who seek to enter it. A useful case study is provided by Edge AI startup Blaize, which is pursuing customers in industrial, smart city, automotive sensor fusion, last-mile delivery, and retail applications with its recently launched Pathfinder and Xplorer system-on-module platforms and accompanying software tools.

Last November I covered Blaize and its silicon and software strategy, and noted that the company's fairly large team has been focused on early customer engagements to gain insights and accelerate adoption. Now the company, backed by industrial heavyweights such as Samsung, Daimler and Denso, is advancing from development into full production and customer deployment. Blaize claims its silicon is designed to be a "no-compromise" platform that delivers the performance customers need, while delivering it at low cost and low power. From what we now know, the company's claims seem to have merit. Let's take a look at what they have recently announced. The recent announcements disclosed availability (sampling now), efficiency ( 2 TOPS/Watt), pricing (starting at $299) and its new AI Studio software which complements the previously announced Picasso SDK.

AI processing is changing the world order among CPU, GPU, and FPGA companies, with a host of AI processor startups joining the fray. The fight was once mostly in data centers, but they've all had to decamp to a new battlefield at the network edge. Driven by that premise, Blaize, an AI processor startup in El Dorado Hills, Calif., is heading straight to the edge with its just-announced AI hardware and software. The market forces sending AI inference to the edge are well understood. Privacy concerns, bandwidth issues (going back and forth between edge to cloud), latency and cost worries drive AI processing more and more edgeward.

Claimed to be the first architecture to enable concurrent execution of multiple neural networks and entire workflows on a single system, while supporting heterogeneous compute intensive workloads, the Graph Streaming Processor (GSP) architecture will be demonstrated at CES 2020 by Blaize. The computing architecture offers advances in energy efficiency, flexibility, and usability, says the company for existing and new artificial intelligence (AI) in the automotive, smart vision, and enterprise computing segments. The Blaize GSP architecture and Blaize Picasso software development platform blend dynamic data flow methods and graph computing models with fully programmable, proprietary SoCs. This allows Blaize computing platforms to exploit the native graph structure inherent in neural network workloads all the way through runtime, says the company. The massive efficiency multiplier is delivered via a data streaming mechanism, where non-computational data movement is minimised or eliminated for what Blaize claims is the lowest possible latency and it reduces both memory requirements and energy demand at the chip, board and system levels.

Start-up Blaize (formerly known as Thinci) has announced details of the first true Graph-Native silicon architecture and software built to process neural networks and enable AI applications. The Blaize Graph Streaming Processor (GSP) architecture enables concurrent execution of multiple neural networks and workflows on a single system. It also supports a range of heterogeneous compute-intensive workloads, says Blaize. According to Blaize, the computing architecture meets the demands and complexity of new computational workloads found in artificial intelligence (AI) applications in automotive, smart vision and enterprise computing segments. The Blaize GSP architecture and Blaize Picasso software development platform blends dynamic data flow methods and graph computing models with fully programmable proprietary SoCs.

A US startup has emerged from stealth mode with a programmable AI chip architecture and software for artificial intelligence and machine learning. Blaize, formerly called Thinci, has backing from automotive companies such as Toyota and Denso, and currently has 325 staff around the world, including two design teams in the UK. The AI chip technology, called a Graph Streaming Processor (GSP), uses a multicore architecture controlled by a state machine. The flow of the machine learning data is determined in the compiler beforehand. This means the compiler and the software development kit (SDK) is a vital part of the development, and the company claims that the architecture can process data ten to a hundred times faster than other AI chips with lower power consumption. The company has developed prototype chips on a multiproject wafer that is being used with the software by fifteen early adopters around the world.

El DORADO HILLS, CA -- November 12, 2019 -- BlaizeTM today emerged from stealth and unveiled a groundbreaking next-generation computing architecture that precisely meets the demands and complexity of new computational workloads found in artificial intelligence (AI) applications. Driven by advances in energy efficiency, flexibility, and usability, Blaize products enable a range of existing and new AI use cases in the automotive, smart vision, and enterprise computing segments, where the company is engaged with early access customers. These AI systems markets are projected to grow rapidly* as the disrupting influence of AI transforms entire industries and AI functionality becomes a "must-have" requirement for new products. "Blaize was founded on a vision of a better way to compute the workloads of the future by rethinking the fundamental software and processor architecture," says Dinakar Munagala, Co-founder and CEO, Blaize. "We see demand from customers across markets for new computing solutions that address the immediate unmet needs for technology built for the emerging age of AI, and solutions that overcome the limitations of power, complexity and cost of legacy computing."