UK

for-the-first-time-since-1882,-uk-will-have-no-coal-fired-power-plants

For the first time since 1882, UK will have no coal-fired power plants

Into the black —

A combination of government policy and economics spells the end of UK’s coal use.

Image of cooling towers and smoke stacks against a dusk sky.

Enlarge / The Ratcliffe-on-Soar plant is set to shut down for good today.

On Monday, the UK will see the closure of its last operational coal power plant, Ratcliffe-on-Soar, which has been operating since 1968. The closure of the plant, which had a capacity of 2,000 megawatts, will bring an end to the history of the country’s coal use, which started with the opening of the first coal-fired power station in 1882. Coal played a central part in the UK’s power system in the interim, in some years providing over 90 percent of its total electricity.

But a number of factors combined to place coal in a long-term decline: the growth of natural gas-powered plants and renewables, pollution controls, carbon pricing, and a government goal to hit net-zero greenhouse gas emissions by 2050.

From boom to bust

It’s difficult to overstate the importance of coal to the UK grid. It was providing over 90 percent of the UK’s electricity as recently as 1956. The total amount of power generated continued to climb well after that, reaching a peak of 212 terawatt hours of production by 1980. And the construction of new coal plants was under consideration as recently as the late 2000s. According to the organization Carbon Brief’s excellent timeline of coal use in the UK, continuing the use of coal with carbon capture was given consideration.

But several factors slowed the use of fuel ahead of any climate goals set out by the UK, some of which have parallels to the US’s situation. The European Union, which included the UK at the time, instituted new rules to address acid rain, which raised the cost of coal plants. In addition, the exploitation of oil and gas deposits in the North Sea provided access to an alternative fuel. Meanwhile, major gains in efficiency and the shift of some heavy industry overseas cut demand in the UK significantly.

Through their effect on coal use, these changes also lowered employment in coal mining. The mining sector has sometimes been a significant force in UK politics, but the decline of coal reduced the number of people employed in the sector, reducing its political influence.

These had all reduced the use of coal even before governments started taking any aggressive steps to limit climate change. But, by 2005, the EU implemented a carbon trading system that put a cost on emissions. By 2008, the UK government adopted national emissions targets, which have been maintained and strengthened since then by both Labour and Conservative governments up until Rishi Sunak, who was voted out of office before he had altered the UK’s trajectory. What started as a pledge for a 60 percent reduction in greenhouse gas emissions by 2050 now requires the UK to hit net zero by that date.

Renewables, natural gas, and efficiency have all squeezed coal off the UK grid.

Enlarge / Renewables, natural gas, and efficiency have all squeezed coal off the UK grid.

These have included a floor on the price of carbon that ensures fossil-powered plants pay a cost for emissions that’s significant enough to promote the transition to renewables, even if prices in the EU’s carbon trading scheme are too low for that. And that transition has been rapid, with the total generations by renewables nearly tripling in the decade since 2013, heavily aided by the growth of offshore wind.

How to clean up the power sector

The trends were significant enough that, in 2015, the UK announced that it would target the end of coal in 2025, despite the fact that the first coal-free day on the grid wouldn’t come until two years after. But two years after that landmark, however, the UK was seeing entire weeks where no coal-fired plants were active.

To limit the worst impacts of climate change, it will be critical for other countries to follow the UK’s lead. So it’s worthwhile to consider how a country that was committed to coal relatively recently could manage such a rapid transition. There are a few UK-specific factors that won’t be possible to replicate everywhere. The first is that most of its coal infrastructure was quite old—Ratcliffe-on-Soar dates from the 1960s—and so it required replacement in any case. Part of the reason for its aging coal fleet was the local availability of relatively cheap natural gas, something that might not be true elsewhere, which put economic pressure on coal generation.

Another key factor is that the ever-shrinking number of people employed by coal power didn’t exert significant pressure on government policies. Despite the existence of a vocal group of climate contrarians in the UK, the issue never became heavily politicized. Both Labour and Conservative governments maintained a fact-based approach to climate change and set policies accordingly. That’s notably not the case in countries like the US and Australia.

But other factors are going to be applicable to a wide variety of countries. As the UK was moving away from coal, renewables became the cheapest way to generate power in much of the world. Coal is also the most polluting source of electrical power, providing ample reasons for regulation that have little to do with climate. Forcing coal users to pay even a fraction of its externalized costs on human health and the environment serve to make it even less economical compared to alternatives.

If these later factors can drive a move away from coal despite government inertia, then it can pay significant dividends in the fight to limit climate change. Inspired in part by the success in moving its grid off coal, the new Labour government in the UK has moved up its timeline for decarbonizing its power sector to 2030 (up from the previous Conservative government’s target of 2035).

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Astronomers discover technique to spot AI fakes using galaxy-measurement tools

stars in their eyes —

Researchers use technique to quantify eyeball reflections that often reveal deepfake images.

Researchers write,

Enlarge / Researchers write, “In this image, the person on the left (Scarlett Johansson) is real, while the person on the right is AI-generated. Their eyeballs are depicted underneath their faces. The reflections in the eyeballs are consistent for the real person, but incorrect (from a physics point of view) for the fake person.”

In 2024, it’s almost trivial to create realistic AI-generated images of people, which has led to fears about how these deceptive images might be detected. Researchers at the University of Hull recently unveiled a novel method for detecting AI-generated deepfake images by analyzing reflections in human eyes. The technique, presented at the Royal Astronomical Society’s National Astronomy Meeting last week, adapts tools used by astronomers to study galaxies for scrutinizing the consistency of light reflections in eyeballs.

Adejumoke Owolabi, an MSc student at the University of Hull, headed the research under the guidance of Dr. Kevin Pimbblet, professor of astrophysics.

Their detection technique is based on a simple principle: A pair of eyes being illuminated by the same set of light sources will typically have a similarly shaped set of light reflections in each eyeball. Many AI-generated images created to date don’t take eyeball reflections into account, so the simulated light reflections are often inconsistent between each eye.

A series of real eyes showing largely consistent reflections in both eyes.

Enlarge / A series of real eyes showing largely consistent reflections in both eyes.

In some ways, the astronomy angle isn’t always necessary for this kind of deepfake detection because a quick glance at a pair of eyes in a photo can reveal reflection inconsistencies, which is something artists who paint portraits have to keep in mind. But the application of astronomy tools to automatically measure and quantify eye reflections in deepfakes is a novel development.

Automated detection

In a Royal Astronomical Society blog post, Pimbblet explained that Owolabi developed a technique to detect eyeball reflections automatically and ran the reflections’ morphological features through indices to compare similarity between left and right eyeballs. Their findings revealed that deepfakes often exhibit differences between the pair of eyes.

The team applied methods from astronomy to quantify and compare eyeball reflections. They used the Gini coefficient, typically employed to measure light distribution in galaxy images, to assess the uniformity of reflections across eye pixels. A Gini value closer to 0 indicates evenly distributed light, while a value approaching 1 suggests concentrated light in a single pixel.

A series of deepfake eyes showing inconsistent reflections in each eye.

Enlarge / A series of deepfake eyes showing inconsistent reflections in each eye.

In the Royal Astronomical Society post, Pimbblet drew comparisons between how they measured eyeball reflection shape and how they typically measure galaxy shape in telescope imagery: “To measure the shapes of galaxies, we analyze whether they’re centrally compact, whether they’re symmetric, and how smooth they are. We analyze the light distribution.”

The researchers also explored the use of CAS parameters (concentration, asymmetry, smoothness), another tool from astronomy for measuring galactic light distribution. However, this method proved less effective in identifying fake eyes.

A detection arms race

While the eye-reflection technique offers a potential path for detecting AI-generated images, the method might not work if AI models evolve to incorporate physically accurate eye reflections, perhaps applied as a subsequent step after image generation. The technique also requires a clear, up-close view of eyeballs to work.

The approach also risks producing false positives, as even authentic photos can sometimes exhibit inconsistent eye reflections due to varied lighting conditions or post-processing techniques. But analyzing eye reflections may still be a useful tool in a larger deepfake detection toolset that also considers other factors such as hair texture, anatomy, skin details, and background consistency.

While the technique shows promise in the short term, Dr. Pimbblet cautioned that it’s not perfect. “There are false positives and false negatives; it’s not going to get everything,” he told the Royal Astronomical Society. “But this method provides us with a basis, a plan of attack, in the arms race to detect deepfakes.”

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World’s first global AI resolution unanimously adopted by United Nations

We hold these seeds to be self-evident —

Nonbinding agreement seeks to protect personal data and safeguard human rights.

The United Nations building in New York.

Enlarge / The United Nations building in New York.

On Thursday, the United Nations General Assembly unanimously consented to adopt what some call the first global resolution on AI, reports Reuters. The resolution aims to foster the protection of personal data, enhance privacy policies, ensure close monitoring of AI for potential risks, and uphold human rights. It emerged from a proposal by the United States and received backing from China and 121 other countries.

Being a nonbinding agreement and thus effectively toothless, the resolution seems broadly popular in the AI industry. On X, Microsoft Vice Chair and President Brad Smith wrote, “We fully support the @UN’s adoption of the comprehensive AI resolution. The consensus reached today marks a critical step towards establishing international guardrails for the ethical and sustainable development of AI, ensuring this technology serves the needs of everyone.”

The resolution, titled “Seizing the opportunities of safe, secure and trustworthy artificial intelligence systems for sustainable development,” resulted from three months of negotiation, and the stakeholders involved seem pleased at the level of international cooperation. “We’re sailing in choppy waters with the fast-changing technology, which means that it’s more important than ever to steer by the light of our values,” one senior US administration official told Reuters, highlighting the significance of this “first-ever truly global consensus document on AI.”

In the UN, adoption by consensus means that all members agree to adopt the resolution without a vote. “Consensus is reached when all Member States agree on a text, but it does not mean that they all agree on every element of a draft document,” writes the UN in a FAQ found online. “They can agree to adopt a draft resolution without a vote, but still have reservations about certain parts of the text.”

The initiative joins a series of efforts by governments worldwide to influence the trajectory of AI development following the launch of ChatGPT and GPT-4, and the enormous hype raised by certain members of the tech industry in a public worldwide campaign waged last year. Critics fear that AI may undermine democratic processes, amplify fraudulent activities, or contribute to significant job displacement, among other issues. The resolution seeks to address the dangers associated with the irresponsible or malicious application of AI systems, which the UN says could jeopardize human rights and fundamental freedoms.

Resistance from nations such as Russia and China was anticipated, and US officials acknowledged the presence of “lots of heated conversations” during the negotiation process, according to Reuters. However, they also emphasized successful engagement with these countries and others typically at odds with the US on various issues, agreeing on a draft resolution that sought to maintain a delicate balance between promoting development and safeguarding human rights.

The new UN agreement may be the first “global” agreement, in the sense of having the participation of every UN country, but it wasn’t the first multi-state international AI agreement. That honor seems to fall to the Bletchley Declaration signed in November by the 28 nations attending the UK’s first AI Summit.

Also in November, the US, Britain, and other nations unveiled an agreement focusing on the creation of AI systems that are “secure by design” to protect against misuse by rogue actors. Europe is slowly moving forward with provisional agreements to regulate AI and is close to implementing the world’s first comprehensive AI regulations. Meanwhile, the US government still lacks consensus on legislative action related to AI regulation, with the Biden administration advocating for measures to mitigate AI risks while enhancing national security.

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Adobe gives up on $20 billion acquisition of Figma

No deal —

Competition probes in the EU and UK made regulatory approval dicey.

Adobe and Figma logos

Adobe has abandoned its proposed $20 billion acquisition of product design software company Figma, as there was “no clear path to receive necessary regulatory approvals” from UK and EU watchdogs.

The deal had faced probes from both the UK and EU competition regulators for fears it would have an impact on the product design, image editing, and illustration markets.

Adobe refused to offer remedies to satisfy the UK Competition and Markets Authority’s concerns last week, according to a document published by the regulator on Monday, arguing that a divestment would be “wholly disproportionate.”

Hours later, the two companies issued a mutual statement terminating the merger, citing the regulatory challenges. Adobe will pay Figma $1 billion in a termination fee under the terms of the merger agreement.

“Adobe and Figma strongly disagree with the recent regulatory findings, but we believe it is in our respective best interests to move forward independently,” said Shantanu Narayen, chair and chief executive of Adobe.

The companies had been battling multiple regulatory challenges, with the EU’s executive body, the European Commission, publishing a statement of objections to the deal last month arguing the takeover could “significantly reduce competition in the global markets.”

Margrethe Vestager, the EU’s competition commissioner, said: “By combining these two companies, the proposed acquisition would have terminated all current and prevented all future competition between them. Our in-depth investigation showed that this would lead to higher prices, reduced quality or less choice for customers.”

Competition regulators around the world have sent mixed signals over the aspirations of Big Tech groups hoping to acquire promising start-ups and potential rivals, at a time when public markets have been largely closed to new listings.

The EU’s antitrust watchdog has made a formal objection to Amazon’s $1.7 billion proposed purchase of Roomba-maker iRobot. However, Microsoft was able to complete its $75 billion takeover of games maker Activision after it made revisions to the deal to appease UK regulators.

Speaking with the Financial Times last week, Figma chief executive Dylan Field said: “It is important that those paths of acquisition remain available because very few companies make it all the way to IPO. So many companies fail on the way.”

Shares in Adobe were up almost 2 percent in pre-market trading. Since the deal was announced, Adobe has turned its focus to embedding generative artificial intelligence into its products by, for example, enabling users to create novel stock imagery with AI.

The huge price that Adobe was willing to pay for San Francisco-based Figma had been seen by critics of the deal as an effort to quash the software giant’s most promising new rival in decades.

The deal, which was first negotiated during the COVID-19 pandemic’s boom in tech investment and announced in September 2022, would have valued Figma at roughly 50 times its annual recurring revenue, and double its last private funding round in 2021.

The companies were expected to appear in front of the CMA to contest the regulator’s provisional findings on Thursday this week.

Under its proposed remedies in November, the CMA said it was considering either prohibiting the deal or demanding the divestiture of overlapping operations, such as Adobe’s Illustrator or Photoshop, or Figma’s core product, Figma Design.

Field said that the latter suggestion left him amazed at “the idea of buying a company so you can divest the company.”

“When I read that document and saw that was one of the proposals, I thought it was quite amusing; it felt like a bit of a punchline to a joke. I was surprised to see that as a proposal from the agency.” In a statement on Monday, Field said he was “disappointed in the outcome.”

Earlier on Monday, the CMA had published the companies’ responses to its provisional findings, which Adobe and Figma said contained “serious errors of law and fact” and took “an irrational approach to the gathering and appraisal of evidence.”

“Requiring a multibillion-dollar global divestment of Photoshop or Illustrator in order to address an uncertain and speculative theory of harm is wholly disproportionate,” they wrote.

© 2023 The Financial Times Ltd. All rights reserved. Not to be redistributed, copied, or modified in any way.

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Musk on how to turn the UK into a ‘unicorn breeding ground’

If you are generally interested in technology, and are not aware by now of the meeting that took place yesterday between Rishi Sunak and Elon Musk during the UK’s AI Security Summit at Bletchley Park, you have probably been living under a rock.

As others have already commented, the session more resembled a fan meeting, or at the very least a club of mutual admiration, than an actual interview. The PM’s fawning giggles were perhaps not entirely suited to the gravity of the occasion bringing the two together (but hey, who are we to judge). 

You have probably also read Elon Musk‘s statements along the lines of “no work will be necessary in the future,” and that any AI safety conference not including China would have been “pointless.” He also predicted that humans will create deep friendships with AI, once the technology becomes… intelligent enough.



But, perhaps less quote friendly or headline-making material, prompted by a question from the Summit’s selected audience, the tech tycoon also discussed what he believes it would take to shift the culture in the UK so that it could become “a real breeding ground for unicorn companies,” and turn being a founder into a more obvious career choice for technical talent. 



“There should be a bias towards supporting small companies,” Musk said, referring to policy and investment. “Because they are the ones that really need nurturing. The larger companies really don’t need nurturing. You can think of it as a garden — if it’s a little sprout it needs nurturing, if it’s a mighty oak it does not need quite as much.” 

After praising London as a leading centre for AI in the world (behind the San Francisco Bay Area), accompanied by some smug nodding from the PM, Musk added that it would take sufficient infrastructure support. 

“You need landlords that are willing to rent to new companies,” Musk said. “You need law firms and accountants that are willing to support new companies. And that is a mindset change.”

He further stated that he believes culturally, in the UK, this is happening, but people just really need to decide that “this is a good thing.” For Brits to become more comfortable with failing might be a more tricky cultural shift to facilitate. 

“If you don’t succeed with your first startup it shouldn’t be a catastrophic sort of career-ending thing,” Musk mused. “It should be more like ‘ok, you gave it a good shot, and now try again.’



“Most startups fail. You hear about the startups that succeed, but most startups consist of a massive amount of work, followed by failure. So it’s a high-risk high reward situation.”

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UK’s first exascale supercomputer project goes to Edinburgh

The UK today said it had selected Edinburgh to host its first exascale next-gen supercomputer, which will be 50 times faster than its current highest capacity system.



The University of Edinburgh will house the country’s new exascale computing facility, which the government says will “safely harness its potential to improve lives across the country.” It will build on the technology and experience from the planned Bristol supercomputer — the AI Research Resource (AIRR), or Isambard-AI. 

“If we want the UK to remain a global leader in scientific discovery and technological innovation, we need to power up the systems that make those breakthroughs possible, said Michelle Donelan, Secretary of State for Science, Innovation, and Technology. 

“This new UK government funded exascale computer in Edinburgh will provide British researchers with an ultra-fast, versatile resource to support pioneering work into AI safety, life-saving drugs, and clean low-carbon energy,” she continued.

Today’s announcement comes hot on the heels of last week’s declaration that the EU will build its first exascale computer in Germany. 

Part of national next-gen computer upgrade project

A brief recap — an exascale supercomputer is a high-performance computing (HPC) system that can perform a billion billion floating point operations per second (this is measured as one exaflop). This kind of computing power can help solve problems in areas such as fusion energy, material science, drug discovery, climate change, and astrophysics. 

As of this summer, there was only one supercomputer with exascale capacity — Frontier in Tennessee, USA. It will be surpassed in 2024 when the 2-exaflop capacity El Capitan comes online in California. 

Currently, the most powerful computer system in the UK is the ARCHER2, also housed in Edinburgh. It has a peak performance of 28 petaflops (a petaflop = one thousand million million flops per second), which doesn’t even land it in the top 10 worldwide. The new exascale system will be approximately 50 times faster. 

“We have already seen the vital work being carried out by ARCHER2 in Edinburgh and this new exascale system, backed by the UK government, will keep Scotland at the forefront of science and innovation,” said Secretary of State for Scotland, Alister Jack. He further added that as well as supporting researchers in work on AI safety, the new project would bring highly skilled jobs and support economic growth for the region.

In the meantime, Bristol will also see the Isambard 3 supercomputer installed later this year. Plans for both the Edinburgh exascale computer and the Bristol AIRR were announced in March, as part of a £900mn investment to upgrade the UK’s next-generation computer capacity. 

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Spotify ‘unfairly held back’ by Google and Apple, CEO says

While on a tour to woo UK lawmakers ahead of the adoption of the Digital Markets, Competition and Consumers Bill, Daniel Ek has taken a swing at big tech’s dominance. 

The Spotify CEO urged the UK to “show leadership” as it prepared to regulate big tech according to its own agenda outside of the EU. However, it is unclear just exactly how much further he expects it to go compared to the bloc’s Digital Markets Act (DMA).

Of course, it is not just concern for the little guy/consumer and their right to access services without the say-so of big tech that has prompted Ek’s charm offensive. In an interview with the Financial Times, the music streaming giant’s boss said that Spotify was being unfairly held back by digital platforms such as Apple because of their position as internet gatekeepers.

“I find it insane that two companies [Apple and Google] essentially control how over 4bn consumers access the internet around the world,” Ek said. “Not only are they dictating the rules, they also compete directly downstream with those providers.”

After the DMA, the DMCC

The Digital Markets, Competition and Consumers Bill (DMCC) is currently at the report stage in the House of Commons. Sarah Cardell, CEO of the UK Competition and Markets Authority (CMA), has described it as a flagship bill which has the potential to be a “watershed moment.”

The bill has three areas of focus: consumer protection, digital markets, and competition. In regards to tech, it will empower the Digital Markets Unit (DMU) within the CMA to oversee and enforce the new digital competition regime. According to Cardell, it will “establish a tailored, evidenced-based and proportionate approach to regulating the largest and most powerful digital firms to ensure effective competition that benefits everyone.” 

Again, it will be interesting to see just how the DMCC will differ from the European Union’s DMA, under which regulators recently revealed a list of designated gatekeepers that would need to ‘open up’ their services to competitors.

Will not ban AI music from Spotify

In addition to his commentary on rules for big tech, Ek voiced concerns that any regulation of artificial intelligence made now would soon become obsolete due to the fast-paced development of the technology. Earlier in the week, he told the BBC that he would not ban AI generated music from his platform. Ek further added that there were valid uses of the tech in making music, but that it should not be used to impersonate human artists without their consent.

The UK government is reportedly pushing AI companies, including OpenAI and Google DeepMind, for greater access to their Large Language Models (LLMs), as it prepares to host the forthcoming global AI summit at Bletchley Park. This will be key to have a better understanding of how the technology works and judge the kinds of risks that will arise. Meanwhile, people on both sides of the negotiations have stated that companies, in turn, are concerned about risks to proprietary product information, as well as potential exposure to cyberattacks. 

The tech regulatory tug-of-war continues.

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UK chip designer Arm valued at $50B ahead of today’s IPO

And thus, after months of anticipation and speculation, the day of Arm’s IPO is upon us. The SoftBank-owned chip design company will begin trading in New York today, Thursday, with shares priced at $51 (€47.51) apiece. This gives Arm a valuation of $52.3bn (€48.7bn). 

Japanese SoftBank intends to hold onto just above 90% of the company. Still, the heavily oversubscribed round is set to raise about $4.9bn for Arm’s owners. Big tech customers of Arm’s designs have shown a massive interest in buying shares, and the banks underwriting the listing closed orders on Tuesday, a day earlier than originally planned. 

Despite being central to the global semiconductor industry, Arm has never made a single computer chip itself. What it makes instead are the blueprints for chips. It then licences the intellectual property and the instruction sets to other companies, be that Apple, Nvidia, Qualcomm, Google, Samsung, Alibaba, or ByteDance. Indeed, since the company was founded in Cambridge, UK, in 1990, ​​Arm estimates that more than 250 billion chips using its technology have been sold globally. 

As one might imagine, despite often being referred to as the Switzerland of semiconductors, this puts Arm right in the middle of the ever increasing complexity of the “chip war” landscape and value chain. There may be bumpy roads ahead with increasing political pressure, and a potential, open source challenger in RISC-V. 

Watershed moment for tech listings

The company’s CEO, Rene Haas, is the first American to run Arm. He is expected to ring the Nasdaq opening bell on Thursday. The company has declined all requests for comments leading up to the big day. Meanwhile, how Arm performs is also set to influence the market for public listings for tech companies going forward, with a number of Silicon Valley startups following the proceedings closely.

At the same time, on Arm’s home soil, investors have not been kind to tech companies that have chosen to list on the London Stock Exchange over the recent years. This is one of the reasons why the crown jewel in the British tech ecosystem — despite months of lobbying from the UK government, decided to focus on a sole listing in New York. 

Sources familiar with the matter told Bloomberg in March this year that while the company had not ruled out a second listing in London down the road, it was “not likely.” However, Tokyo-based SoftBank is making good on its promise when purchasing the business in a $32bn deal in 2016, and is leaving the headquarters in Cambridge.

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‘World’s most accurate’ startup data platform to identify gaps in AI ecosystem

Today, the Saïd Business School at the University of Oxford, along with early-stage VC OpenOcean, released what they call “the world’s most accurate open access startup insights platform” — the O3

The platform is the result of three years of research from Oxford Saïd and 13 years of experience of data economy investing from OpenOcean. It leverages public and private data sources and is meant to help improve decision making across the UK tech ecosystem, through “granular data on startups and their technology stack, solutions, and go-to-market strategies.” 

“In my time in venture capital, far too often the choice of which startups receive funding has come down to instinct and opportunistic use of data, rather than accurate definition and comparison of startups,” said Ekaterina Almasque, General Partner at OpenOcean. “We wanted to change that, creating a platform that cuts through the noise, and removes bias from decision-making.” 

The O3 platform has already screened 16,913 UK startups according to a unique taxonomy developed by Oxford Saïd. For an initial analysis, it has looked specifically at high-growth startups that use or facilitate AI (close to 1,300), and has come up with some interesting findings about the sector.

AI startups a small portion of UK tech ecosystem

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The UK government has asserted that it is going to make the country an AI powerhouse. However, thus far, the number of UK startups with a pronounced AI focus make up less than 10% of the ecosystem. 

Mari Sako, Professor of Management Studies at Oxford Saïd, believes that the O3 will enable policymakers, researchers, founders, and investors to clearly identify gaps and opportunities in the AI ecosystem. “We believe this platform has immense potential to aid innovators in making informed decisions based on sound data, and to boost research on AI,” Sako said.  

UK fintech is generally a top investment destination in Europe, but when it comes to AI, the health tech startup segment receives more funding (£2.6bn vs. £3.4bn, respectively). 

Startups using AI for recognition tasks, including but not exclusive to facial recognition, have collectively raised the most funding (£6bn). Meanwhile, among the least funded are those focusing on privacy protection (£1.2bn). 

The analysis has also uncovered, perhaps unsurprisingly, a significant bias towards London for startup fundraising. However, there is also notable support in Bristol, Oxford, and Cambridge. 

According to the originators of the platform, the UK is only the beginning. “We want to see it expand to cover more markets and geographies,” Almasque continued. “It is a community driven project, built on open access, where the more stakeholders participate, the more powerful is the common knowledge.”

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UK commits £100M to secure AI chip components

In an intensifying global battle for semiconductor self-sufficiency, the UK will reportedly spend £100mn of taxpayer money to buy AI chip technology from AMD, Intel, and Nvidia. The initiative is part of the  UK’s intention to build a national AI resource, but critics say it is too little, too late. 

As reported by The Guardian, a government official has confirmed that the UK is already in negotiations with Nvidia for the purchase of up to 5,000 graphic processing units (GPU). However, they also stated that the £100mn was way too little compared to what for instance the EU, US, and China are committing to the growth of a domestic semiconductor industry.

The UK accounts for only 0.5% of global semiconductor sales, according to a Parliamentary report. In May this year, the government announced it would commit £1bn over 10 years to bolster the industry. In comparison, the US and the EU are investing $50bn (€46bn) and €43bn, respectively. 

The idea, Rishi Sunak said at the time, is to play to the UK’s strengths. This means to focus efforts on areas like research and design, the PM stated. In turn, this can be contrasted to the approach of building large fabs, such as the ones Germany is spending billions in state aid to make a reality. 

UK’s AI summit at historic computer science site

Alongside a push (no matter its size) toward more advanced AI-powering chip capabilities, the UK recently announced the time for its much-publicised AI safety summit. The meeting between officials from “like-minded” states, tech executives, and academics will take place at Bletchley Park, situated between Cambridge and Oxford, at the beginning of November. 

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The site is considered the birthplace of the first programmable digital computer, that helped crack the Enigma encryption machine used by the Nazis, essentially tipping the scales of World War II. Today, it is home to the National Museum of Computing, run by the Bletchley Park Trust. 

Meanwhile, the race to secure components for chips, or the chips themselves, that can power AI systems, such as large language models (LLM), is accelerating. According to the Financial Times, Saudi Arabia has bought at least 3,000 of Nvidia’s processors, especially designed for generative AI. Its neighbour, the UAE, has far-reaching AI ambitions of its own, also having purchased thousands of advanced chips and developing its own LLM.  

Meanwhile, Chinese internet giants have reportedly rushed to secure billions of dollars worth of Nvidia chips ahead of a US tech investment ban coming into effect early next year. It is still unclear whether the UK will invite China to the gathering at Bletchley Park in November. The geopolitics and tech diplomacy of semiconductors could be entering its most delicate phase to date.

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UK algorithm startup closes in on quantum advantage

Quantum computing holds a lot of promise. The question is when the hyped and indeed potentially revolutionising technology will begin to deliver on it. According to UK quantum startup Phasecraft, it’s not that far off. The secret? Algorithms that can work on today’s “imperfect” quantum computers, without having to wait for the very tricky hardware to draw level. 

You could forgive the quantum sceptics for their “I’ll believe it when I see it” attitude. To date, no quantum computer or algorithm has been able to solve any problem of actual significance. However, according to Ashley Montanaro, Phasecraft CEO and University of Bristol professor of quantum computation, the day of quantum advantage could now be merely a couple of years away.

“The goal of Phasecraft is to develop the quantum algorithms and software that will let us really make the most out of today’s quantum computers and the sorts of quantum computers we’re going to have in the next few years, as opposed to the next 10 or 20,” Montanaro tells TNW in an interview. 

Material discovery for energy transition

The ability of quantum computers to leverage quantum bits (qubits) in superposition and entanglement allows them to process vast amounts of information simultaneously. This means they could offer giant leaps in things like factoring large numbers for cryptography, and simulating quantum interactions in chemistry and materials science. 

Phasecraft is focusing its efforts on algorithms that can facilitate the discovery of new materials important for the clean energy transition. Rather than relying on experimental discovery which can take decades, quantum algorithms can simulate interactions on the quantum level, predicting how materials will behave under various conditions. 

“Because the algorithms on the standard computer are not accurate enough, you would need to test them out in the lab,” Montanaro says. “[Quantum computing] could reduce the time of testing out a new material from months to minutes, because you’re doing it within the computer rather than in the lab with the whole experimental project.”

Through what it calls a “radical reimagining” of existing algorithms, the London- and Bristol-based startup says it has already developed a software pipeline which delivers an improvement of 1,000,000x or more in comparison. 

Additionally, it will be able to run on what Phasecraft says are “within touching distance” of today’s so-called Noisy Intermediate Scale Quantum, or NISQ, devices. To that effect, Phasecraft has partnered with powerhouses Google, IBM, and Rigetti, who are investing large sums into quantum hardware development. It is currently the only quantum software developer to work with all three. 

Deep tech VC backing

Phasecraft was founded by Professors Ashley Montanaro, CEO, the aptly named CTO Toby Cubitt, and director John Morton in 2019, and currently employs 20 people. Spun out of the University of Bristol and UCL, the company just raised £13mn in Series A funding, led by Silicon Valley deep tech VC Playground Global.

Each of the founders have been at the forefront of quantum research for the past couple of decades, and the company has already published 17 scientific papers. 

The Phasecraft team posing together on a lawn
The Phasecraft team is divided between London and Bristol. Credit: Phasecraft

The latest funding round brings the total capital raised to £17.25mn in venture funding, plus an additional £3.75mn in grant funding from the likes of Innovate UK and the European Research Council. 

Montanaro states that the company is incredibly excited to work with Playground, who was joined in the round by existing investors Episode1, Parkwalk Advisors, LCIF, and UCL Technology Fund, as well as London-based AlbionVC.

UK algorithm startup closes in on quantum advantage Read More »

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UK may emulate US ban on China tech investments

On Wednesday, US President Joe Biden unveiled an executive order banning new investments in certain tech sectors in China, citing security risks. The order is set to come into effect next year, and the US will be waiting to see if its closest ally will follow suit. However, for now, the UK says it will consider the measures taken by its transatlantic partner, as it continues to evaluate security implications.

“This executive order on outward investment gives important clarity on the US approach,” a spokesperson for the government said in a statement shared with the Financial Times earlier today. “The UK will consider these new measures closely as we continue to assess potential national security risks attached to some investments.”

The forthcoming ban includes new private-equity, venture-capital and joint-venture investments in advanced computer chips, quantum computers, and certain AI systems. Furthermore, companies already doing business in China will need to notify the government of new investments in the sectors. The goal is to hinder the Chinese military from obtaining both US technology and money. 

Needless to say, China did not respond kindly to the order, stating it considered the measures to be “blatant economic coercion and technological bullying.” 

Tech trade balancing act

This leaves Rishi Sunak and his government with a bit of a diplomatic conundrum. In the declaration on cooperation on export controls between the US and the UK signed in June, the parties agreed to undertake a review of export control, focusing on “end users of concern.” Britain further said it would update its control regime to better “tackle sensitive technology transfers.”

The UK has also stated it is ready to remain closely tied to the approach of the US, especially when it comes to military technologies, and “respond effectively” to any impact British capital and technology could have on shared security concerns. 

Mainland China is not a huge destination for UK foreign investment, attracting £10.7bn (€12.4bn) in 2021, compared to the £461.4bn (€537.5bn) that flowed westward across the Atlantic. However, in an update on the government’s foreign policy plan from May, Britain says it will endeavour to shield critical supply chains, but also emphasises the importance of UK-China trade for the British economy. 

As technology, economics, and national security is becoming ever increasingly intertwined, it seems we are going to need a whole new school of high-stakes tech diplomacy.

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