Graphcore: From Unicorn to SoftBank Acquisition – What Happened?

Graphcore had plans for $120 million ‘brain-scale’ supercomputers in 2024. In February 2024, PitchBook estimated a 97% probability that Graphcore would go public. Instead, the company was sold to SoftBank in July 2024, reportedly for $500 million – less than the total investments it received over the years. Once a unicorn with a $2.8 billion valuation and ambitions to overshadow NVIDIA, Graphcore found itself scrambling to pay salaries. As we continue to investigate AI infrastructure unicorns, particularly AI chip companies, let’s explore what happened to this once-promising semiconductor company, why it proved almost impossible to beat NVIDIA, what’s happening with the “brain-scale” computer, what SoftBank has in mind with this acquisition, and what the Japanese god of creation has to do with it. Read on!

In today’s episode:

1. The initial idea – being ahead of time

2. Tough beginnings

3. A windfall of investments

4. What went wrong? 

5. What did Graphcore build throughout the years?

6. There was another ambition – “Good Computer”

7. But there was always something off, and then the investors started to write them off as an investment

8. Graphcore in SoftBank’s ARM

9. Conclusion

The initial idea – being ahead of time

Nigel Toon and Simon Knowles sold their company, Icera, to NVIDIA in 2011 for $435 million. Icera specialized in creating advanced 3G cellular modem chips, which played a crucial role in mobile communications technology. Following this successful sale, Toon and Knowles believed they could develop something that NVIDIA hadn’t yet achieved. In 2012, they started to discuss what they could build to beat NVIDIA. Knowles believed that the main obstacle in AI development was the inefficiency of computer chips, like CPUs and GPUs, which aren't designed to mimic human intuition. Instead of efficiently processing information, these chips analyze massive amounts of data, consuming vast amounts of energy. The two partners decided to design chips – Intelligence Processing Unit (IPU) –  that think more like human brains to improve AI efficiency and reduce energy usage. At that time, they argued that overcoming the hardware limitations was more crucial for advancing AI than just focusing on complex software.

“We wanted to build a very high-performance computer that manipulates numbers very imprecisely,” says Knowles. The founders assert that they recognized in 2012 that AI was going to be a huge thing. They understood it would need new types of processors. 

They believed that processors specifically designed for AI could outperform more general-purpose chips across a variety of ML tasks. 

“NVIDIA was still pretty small at the time. We thought we could compete with them,” says Toon. Toon explains that unlike traditional programming where machines follow step-by-step instructions, Graphcore's chips enable machines to learn autonomously. He likens this shift to the revolutionary emergence of microprocessors in the 1970s, suggesting that Graphcore is reinventing the approach to computing, much like Intel did back then.

Herman Hauser (co-founder of Acorn Computers that later became ARM) believed in Toon and Knowles from the very beginning, hoping that they would unleash the third wave of computing (CPU in the 1970s being the first, GPU in the 1990s being the second). 

After such endorsement, it was hard not to start the company. In 2013, the Graphcore project began in stealth mode, with an official launch in 2016 in Bristol, UK. This place is sometimes called a “Deep Tech Powerhouse” and is part of the Silicon Gorge region. Companies innovating in Bristol traditionally receive financial support from the British government. 

Tough beginnings

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