For the last decade, a “smart phone” was defined by its ability to run applications locally on the device. These days, however, “smart” means features powered by AI, with intelligent applications such as enhanced computational photography, voice processing and gaming with AR features. It appears that Qualcomm’s next generation mobile processors are about to take …
As we approach the end of a year full of promises from AI startups, a few companies are meeting their promised 2019 launch dates. These include Intel, with its long-awaited Nervana platform, UK startup Graphcore and the stealthy Groq from Silicon Valley. Some of these announcements fall a bit short on details, but all claim …
Intel, GraphCore And Groq: Let The AI Cambrian Explosion Begin Read More »
When the mlperf (machine learning performance) organization released the first standardized AI training benchmarks, which NVIDIA dominated last December, we were somewhat disappointed that only a few companies, namely NVIDIA, Google and Intel, were able to muster the working chips and software needed to complete the benchmarks. Last week, the open-source mlperf community released the first round of …
Throughout 2020, a wave of AI hardware startups will launch their companies and products. Cerebras started this wave with its wafer-scale engine last September. This week, Intel announced its AI chips from Nervana, Groq (founded by the inventors of Google TPU) announced its quadrillion ops per second TSP, and Graphcore announced that its chip is available on Microsoft Azure …
As I covered in a recent article on the status of startups building chips for AI, the AI accelerator market will become quite crowded over the next 12-18 months. Not to be outdone, Arm is now extending its neural network processor family, adding logic designs for mid-range and entry-level devices to the flagship Ethos-N77, which targets higher-end …
A few months ago, I published a blog that highlighted Qualcomm’s plans to enter the data center market with the Cloud AI100 chip sometime next year. While preparing the blog, our founder and principal analyst, Patrick Moorhead, called to point out that Qualcomm , not NVIDIA , probably has the largest market share in AI chip volume thanks to its leadership …
The second AI HW Summit took place in the heart of Silicon Valley on September 17-18, with nearly fifty speakers presenting to over 500 attendees (almost twice the size of last year’s inaugural audience). While I cannot possibly cover all the interesting companies on display in a short blog, there are a few observations I’d …
Smartphones today are the pervasive interface for some three billion people to communicate, take photos and videos, and access personal data and applications—all of which are increasingly dependent on AI and Deep Learning. Consequently, mobile processors must accelerate a wide range of AI features in applications, including image processing, voice recognition, translation and gaming. It …
NovuMind is a Silicon Valley startup that builds full-stack Artificial Intelligence (AI) solutions, AI models, algorithms, boards, chips, and intellectual property for both cloud and edge applications. The company focuses on AI inference where a trained deep neural network is used to process images, sound, speeches and other types of information. The market for inference …
RESEARCH PAPER: NovuMind: An Early Entrant In AI Silicon Read More »
Artificial Intelligence (AI) and High-Performance Computing (HPC) are both computationally-intensive workloads. They demand fast central processing units (CPUs), accelerators, very large data sets, and fast networking to support the high degree of scaling typically required. All this fast hardware can be difficult to manage and expensive. AI and HPC adopters must try to minimize costs …
RESEARCH PAPER: AI And HPC: Cloud Or On-Premises Hosting Read More »
Machine Learning (ML) and Artificial Intelligence (AI) will impact practically every application in every industry in the coming few years. Modern applications are increasingly delivered as cloud-based services and as a result, Software-as-a-Service (SaaS) and cloud-based application vendors can now deliver the competitive benefits of AI to their customers. Click on the logo to download …
Artificial Intelligence (AI) is one of today’s fastest growing technologies. Used to derive valuable insights from mountains of data, AI solves problems far more efficiently and accurately than was previously possible with traditional programming techniques. AI is transforming science and businesses around the world from cancer research to virtual assistants to autonomous vehicles. However, many …
RESEARCH PAPER: Dell Technologies: Ready For Artificial Intelligence Leadership Read More »
Modern data scientists have an insatiable appetite for more performance to train and run deep neural networks (DNNs) for artificial intelligence (AI). In fact, research by Open.ai has shown DNNs are doubling their performance requirements every three and a half months compared to the traditional Moore’s Law rate for central processing units (CPUs), which have …
RESEARCH PAPER: Wave Computing: Designed To Scale Read More »
Artificial intelligence (AI) is a transformative technology that will change the way organizations interact and will add intelligence to many products and services through new insights currently hidden in vast pools of data. In 2017 alone, venture capitalists invested more than $11.7 billion in the top 100 Artificial Intelligence startups, according to CB Insights, and …
RESEARCH PAPER: The Artificial Intelligence Starter Guide For IT Leaders Read More »
Artificial intelligence (AI) is delivering new insights − previously hidden in vast pools ofdata − to add intelligence to many products and services that ultimately transform the way organizations and machines interact. While human-like intelligence will remain the stuff of fantasy novels and movies for the near future, most organizations should explore incorporating AI into …
RESEARCH PAPER: A Practitioner’s Guide To Artificial Intelligence Read More »
Historically, numerical analysis has formed the backbone of supercomputing for decades by applying mathematical models of first-principle physics to simulate the behavior of systems from subatomic to galactic scale. Recently, scientists have begun experimenting with a relatively new approach to understand complex systems using machine learning (ML) predictive models, primarily Deep Neural Networks (DNN), trained …
RESEARCH PAPER: Synthesis Modeling: The Intersection Of HPC And Machine Learning Read More »
