The world has experienced three great industrial revolutions over the past 100 years, driven by steam, electricity and then transistors. Now, Artificial Intelligence (AI) is poised to drive the next great wave of technological evolution.
People – and businesses – are generating torrents of data every day, which in turn is changing the way we work, play, communicate and even shop. AI is made possible by high-performance “super computers” that are able to use this data to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. And with AI expenditure expected to reach $46 billion by 2020, according to an IDC report, there’s no sign of the technology slowing down.
The general benefit of AI is that it replicates the decisions and actions of humans without being impacted by human shortcomings, such as fatigue, illness or distractions. It is also easier for companies to achieve more consistent performance across multiple AI machines than it is across multiple human workers. AI simply helps reduce errors and enables a greater degree of accuracy and precision. Although AI offers numerous benefits and can drive businesses significantly, it has some risks as well.
An increasing number of companies are trying to jump into the AI space and offering AI powered solutions to empower systems and business workflows.
Wave Computing is amongst the few of the world’s leading AI solution providers that offer assured deep learning computing systems. The Silicon Valley based company is renowned for its innovative system solutions that leverage dataflow technology to provide high-performance training and high-efficiency inferencing at scale, enabling enterprises to drive better business value from their data. Wave Computing is revolutionizing AI and deep learning with its dataflow-based systems.
Delivering Prolific AI Powered Computing Systems with Superior Efficiency
Unlike other start-ups in the AI hardware space, which are still in early stages of developing or defining their product, Wave Computing is already starting early testing and installation of its first-generation AI product, and is now focused on ensuring its solutions work seamlessly with its customers’ environments. The company’s deep learning systems leverage its unique dataflow technology to eliminate the need for a co-processor (e.g., a CPU or GPU), offering high-performance, high-efficiency training and inferencing computing solutions that scale for any implementation.
Wave Computing is bringing deep learning to the data, wherever the data is—from the datacenter to the edge of the cloud. Its first product, a ‘plug and play’ dataflow appliance, is ideal for data scientists that want to experience faster machine learning without the need for IT involvement – either from a budgetary or technical support perspective.
The Wave dataflow appliance is purpose-built for in-office environment constraints such as space, power and cost, while outperforming existing datacenter servers for machine learning workloads. Ideal for both Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs), it is a complete system that enables data scientists to get rolling on their machine learning workloads right out of the box.
Turning Vision into Reality
The success of any organization depends on the ability of its leaders to convert their vision into reality. If the leaders are capable of encouraging every single employee of their organization, and incepting an astute team of professionals that share the same vision, they can achieve any desired target in an expected time period. Derek Meyer is a perfect example of such visionary leadership.
Derek Meyer is the CEO of Wave Computing. He brings more than 20 years of executive management, corporate strategy, product development and go-to-market experience to Wave. He has been instrumental in leading the company’s initiatives to deliver the world’s first dataflow-based solutions for the rapidly expanding deep learning market, spanning the datacenter to the edge.
Providing World’s Fastest Dataflow Computer for Machine Learning
Machine learning is redefining the way that enterprises do business, enabling organizations to solve complex business problems with AI and deep learning. Wave Computing’s revolutionary new AI appliance delivers orders of magnitude improvement in neural network performance over existing legacy GPU based systems, providing blazingly fast results and improved accuracy that enables faster data driven insight.
Converting Challenges into Opportunity
Datacenter-centric AI applications today need many weeks to train using coprocessors such as GPUs, only to require a different architecture for inferencing at the edge. The lack of a common AI platform, spanning from the datacenter to the edge of the cloud, slows market growth and reduces productivity of data scientists.
Converting this challenge into opportunity, Wave Computing has acquired MIPS Tech, Inc. (formerly MIPS Technologies), a global leader in RISC processor Intellectual Property (IP) and licensable CPU cores. The acquisition will accelerate Wave’s strategy of offering AI acceleration from the datacenter to the edge of cloud by extending the company’s products beyond AI systems to now also include AI-enabled embedded solutions.
While explaining about the new acquisition, Derek Meyer, CEO of Wave Computing asserts, “This acquisition of MIPS allows us to combine technologies to create products that will deliver a single ‘datacenter-to-edge’ platform, ideal for AI and deep learning. We’ve already received very strong and enthusiastic support from leading suppliers and strategic partners, as they affirm the value of data scientists being able to experiment, develop, test and deploy their neural networks on a common platform.”
A Vision to Bestow AI Industry with Fastest and Most Scalable Solutions
Wave Computing’s vision is to deliver AI systems that benefit all. Since its inception in 2011, the experts at Wave have endeavored to bestow the AI industry with the fastest and most scalable dataflow-based deep learning solutions. The company has begun initial testing and installation of its ground-breaking products and is expanding its roadmap of AI system solutions to bring AI to anywhere the data is, from the datacenter to the edge of cloud.