Starting from a single cell and shaped by nearly 4 billion years of evolution, the human brain is perhaps nature's greatest achievement. Our brain is an incredibly complex computing device with approximately 100 billion neurons and more than 100 trillion parameters in a biological-neural-network system that delivers a level of compute yet to be matched by any silicon computers. Today, we are revealing that Graphcore is developing an ultra-intelligence AI computer that will surpass the parametric capacity of the brain. The computer science pioneer Jack Good* was the first person to describe a machine that would exceed the capability of our brain in his 1965 paper, Speculations Concerning the First Ultra-Intelligent Machine. Named in honour of Jack Good, Graphcore will deliver by 2024 the world's first ultra-intelligence AI computer that we are calling the Good computer.

Graphcore CTO and co-founder Simon Knowles delivered a keynote talk during the IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) on June 15, 2022. In his keynote, Simon provided an overview of the current state of AI and outlined the path to achieving human-scale (or even superhuman) artificial intelligence with current or near-future technology. For more on the Good Computer, read Graphcore announces roadmap to Ultra-Intelligence AI supercomputer.

European AI leaders, Graphcore and Aleph Alpha will work together on research and deployment of Aleph Alpha's advanced multi-modal models on current IPU systems and the next-generation Good Computer, thanks to a new partnership between the two companies. Under the agreement, engineers and researchers from Graphcore and Aleph Alpha will work together to co-optimize their respective technologies for pre-training, fine-tuning, and inference of next generation multi-modal language and vision models. Aleph Alpha has received widespread acclaim for its highly versatile Luminous AI model with up to 200bn parameters, with its multi-modal functionality. Luminous enables unique opportunities for customers in a wide range of language and vision fields such as image recognition, knowledge management, document processing, text generation as well as powerful conversational AI applications. Graphcore's made-for-AI Intelligence Processing Unit (IPU) systems accelerate artificial intelligence workloads across industries as diverse as finance, physics, pharmacology, and meteorology.

Graphcore is continuing to build out its AI applications and services ecosystem, launching a new partnership with AI platform company Pienso to make its powerful text analysis solution available on IPUs in the cloud. Pienso uses natural language processing to help businesses extract actionable insights from written text such as comments posted on social media, transcripts of customer service phone calls, news articles and documents. Pienso Graphcore is aimed at enterprise users such as media and entertainment companies, consumer internet - including social networks and e-commerce businesses, telecoms providers, and anyone trying to get high quality, high speed insights from large amounts of written data. No coding or ML skills are needed to build and run models in Pienso, meaning it can be used by subject matter experts and strategic decision makers within a business, removing reliance on in-demand AI engineers. Thanks to the IPU's designed-for-AI architecture and world leading performance in Natural Language Processing, Pienso runs considerably faster and with finer granularity and precision on IPUs than on other compute platforms; a performance gain that makes an already powerful solution truly transformative for its users.

How do you build a computer capable of delivering artificial intelligence processing power on par with the human brain? With AI progressing at pace, the prospect of models that use a greater number of parameters than their biological counterparts is tantalisingly close. An important determinant of when we reach that meaningful milestone is the available compute. In this keynote talk to the World Artificial Intelligence Cannes Festival, Graphcore CTO and Co-founder Simon Knowles discusses the road to "Ultra-Intelligence" and how Graphcore hardware and software systems will enable the advent of Exascale AI computing. For more on the Good Computer, read Graphcore announces roadmap to Ultra-Intelligence AI supercomputer.

LabGenius is engaged in AI-driven scientific research that could only have happened at this moment in time, and the cause couldn't be more important. Today, the company is focused on accelerating the discovery of advanced treatments for cancer and inflammatory diseases, but the principles can be applied far more widely. Using a combination of artificial intelligence, synthetic biology and laboratory automation, the London-based biotech company is developing next-generation antibody therapeutics. The technologies and techniques involved have only recently reached the level of maturity needed for this ambitious undertaking. So, when IPU systems halved the compute time needed to run crucial AI model training, LabGenius' researchers realised that they had found a new and important tool in the race to innovate.

Addressing the Hot Chips 2021 conference, Graphcore co-founder and CTO Simon Knowles delivers a detailed technical keynote on the design and capabilities of the ColossusTM GC200 Intelligence Processing Unit (IPU). Simon outlines the need for a specialist AI processor as a means of unlocking new directions in AI research. He also discusses the importance of sparse computation as a means of handling the multi-trillion parameter models that will be required for human-level machine intelligence. Design features of the IPU, covered in Simon's talk, include:

Machine intelligence is a unique computational workload with distinctly different characteristics to HPC algorithms or graphics programs. With the slowing down of Moore's Law and model sizes on the rise, there is a need for specialised machine learning hardware designed to run AI workloads efficiently. Phil Brown, Graphcore's Director of Applications, recently spoke to Founder of Weights & Biases, Lukas Biewald, about the role of AI processors such as the IPU in driving forward progress in machine intelligence, from enabling sparsity to accelerating BERT. Pursuing new approaches to machine learning can be a challenge, particularly once AI workloads move from pilot to production. At scale, even a slight drop in performance can be costly.

Today, Graphcore is proud to take the next step in our commitment to helping customers accelerate their innovation and harness the power of AI at scale. Together with Cirrascale Cloud Services, we have built something totally new for AI in the cloud, with the first publicly available Mk2 IPU-POD scale-out cluster, offering a simple way to add compute capacity on-demand, without the need to own and operate a datacentre. We recognise that the tremendous opportunity offered by AI brings with it a unique set of computing challenges; model size is growing rapidly, and the bar for accuracy is constantly being raised. If customers are to take full advantage of the latest innovations, they need a tightly integrated hardware and software system built specifically for artificial intelligence. Graphcloud is a secure and reliable IPU-POD family cloud service that allows customers to access the power of Graphcore's Intelligence Processing Unit (IPU), as they scale from experimentation, proof of concept and pilot projects to larger production systems.

Sensoro - a worldwide leader in IoT and smart sensor technology - has chosen Graphcore systems to deliver the AI compute behind its latest environmental and safety monitoring systems. Graphcore IPUs will power a range of new Sensoro solutions, designed to help towns and cities become safer, greener places to live. AI solutions trained on data from smart sensors are emerging as an essential tool in the management of modern, urban environments as they transition to more sustainable forms of energy and transportation, while also dealing with the effects of climate change. Sensoro founder and CEO Tony Zhao said: "Graphcore's IPU systems provide an efficient and easy-to-use computing platform for our urban ESG solution, and solve the computing power bottleneck that we have faced for a long time. "The efficiency of Graphcore IPUs and Poplar's ease of use accelerates the development, optimization and deployment of multiple AI models, and gives us a computing foundation from which we can explore further innovative AI solutions.