John Schulman, co-founder of OpenAI, has departed the company for rival Anthropic. Schulman announced his decision on social media, citing a desire to focus more on AI alignment and return to hands-on technical work.
OpenAI is undergoing significant personnel shifts. Greg Brockman, another co-founder and President, is taking a sabbatical until the end of the year. Meanwhile, product manager Peter Deng has also left the firm.
Earlier this year, other key figures exited OpenAI. Chief scientist Ilya Sutskever departed in May, and founding member Andrej Karpathy left in February to start an AI-integrated education platform. AI safety leader Aleksander Madry was reassigned to a different role in July.
These changes come amid renewed legal challenges from Elon Musk, another OpenAI co-founder. Musk, who left OpenAI three years after its inception, has revived a lawsuit against the company, accusing it of prioritising profits over the public good.
Mainland China has seen a significant surge in AI company registrations, with over 237,000 new firms added in the first half of this year, according to Qichacha, a corporate database platform. The increase in AI companies brings the total number of AI-related companies to 1.67 million due to Beijing’s dedicated efforts to promote AI development.
Notably, almost 90% of these companies, amounting to over 1.48 million, were established after 2017. This surge followed the State Council’s publication of the Next Generation Artificial Intelligence Development Plan, aiming to position China as a global leader in AI technology.
The boom in AI firms highlights China’s burgeoning unicorn landscape, producing four prominent ‘AI tigers’ – Baichuan, Zhipu AI, Moonshot AI, and MiniMax – each securing billions in investments. However, the fierce competition in the sector has also led to a decline in operational AI companies, with only about 419,000 of the new enterprises from last year still active.
Despite the competitive pressures, Beijing continues to bolster the AI industry through supportive policies. Premier Li Qiang introduced the AI Plus initiative at the Two Sessions earlier this year, aiming to integrate AI technology across traditional industries to enhance efficiency and drive economic growth.
Tencent has participated in a $300 million financing round for the Chinese AI startup Moonshot, boosting the company’s valuation to $3.3 billion. The investment aligns with the strategy of Alibaba, another major tech company, which is also backing promising AI ventures. Gaorong Capital and existing investor Alibaba also took part in this funding round.
Moonshot, founded in Shanghai in March 2023, is one of the ‘Six Little Dragons,’ a group of rapidly growing Chinese AI startups aiming to compete with the likes of OpenAI in the US. Earlier this year, Alibaba led a $1 billion funding round for Moonshot. Both Alibaba and Tencent hold stakes in most of these six companies, which include Baichuan and MiniMax.
Recent months have seen significant capital inflows into Chinese AI firms, with major companies and venture capitalists investing heavily to establish a strong presence in the AI market. Baichuan, another member of the ‘Six Little Dragons,’ recently completed a funding round, securing approximately 5 billion yuan with contributions from Alibaba, Tencent, Xiaomi, and other notable investors.
China has launched a $40 billion state investment fund to boost its semiconductor industry, a move aimed at countering US restrictions on semiconductor exports. The fund is part of a broader effort to enhance domestic AI development and secure a leading position in the global AI market.
The London-listed bank, Lloyds Banking Group, has appointed Rohit Dhawan, a former executive at Amazon Web Services (AWS), as its first group director of AI and analytics. With a PhD in AI from the University of Sydney, Dhawan previously led data and AI strategy for AWS across the Asia-Pacific region, where he played a key role in implementing AI in customer and operational processes.
Rohit’s arrival marks a significant step in Lloyds’ ambition to embed AI deeply into its operations. Ranil Boteju, the bank’s chief data and analytics officer, highlighted Dhawan’s extensive experience in delivering technology-driven change at scale and speed. The new director is expected to enhance AI outcomes across various business priorities, ensuring a consistent and strategic integration of AI capabilities.
This appointment is part of Lloyds’ broader push to bolster its technology and data teams. So far in 2024, the bank has hired around 1,500 specialists, bringing the total to over 4,000 new recruits in the last two and a half years. Dhawan expressed his enthusiasm for advancing Lloyds’ ambitious AI strategy, aligning it with the Group’s goal to help Britain prosper.
Despite these strategic advancements, Lloyds has faced financial challenges. The bank reported a 28 per cent drop in net interest income for the first quarter of 2024, primarily due to higher operating costs and peaking interest rates. This resulted in a pre-tax profit of £1.63 billion, consistent with forecasts. Additionally, Lloyds’ shares fell by 2.64 per cent to 53.88p in early afternoon trading on Monday.
Scientists have developed GROVER, an AI model trained to decode human DNA. This innovative tool, created by a team at the Biotechnology Center of Dresden University of Technology, treats DNA as a text, learning its rules and context to draw out functional information from sequences. Published in Nature Machine Intelligence, GROVER has the potential to revolutionise genomics and accelerate personalised medicine.
Understanding DNA’s complex language has been a longstanding challenge. While only 1–2% of the genome consists of genes that code for proteins, the rest contains sequences with multiple functions, many of which remain a mystery. Dr. Anna Poetsch and her team believe AI can help unravel these non-coding regions. GROVER, trained on a reference human genome, has shown the ability to predict DNA sequences and extract contextual information, such as identifying gene promoters and protein binding sites.
GROVER’s development involved creating a DNA dictionary. Using a method inspired by compression algorithms, the team analysed the genome to find common multi-letter combinations, fragmenting the DNA into ‘words’ that improved GROVER’s predictive accuracy. This approach distinguishes GROVER from previous attempts and enhances its ability to decode the genetic language.
Dr. Poetsch and her colleagues are optimistic about GROVER’s impact on genomics. By understanding the rules of DNA through a language model, they hope to uncover deeper biological meanings, advancing both genomics and personalised medicine. GROVER promises to unlock the layers of genetic code, revealing crucial information about human biology, disease predispositions, and treatment responses.
The Olympic Games represent the pinnacle of any athlete’s career and will always be the primary competition for numerous reasons. However, what happens when AI intervenes in organisation, logistics, data collection, event broadcasting, and the sustainability of the competition?
The Olympic AI agenda, launched by the International Olympic Committee, aims to enhance the overall experience for all participants. Paris hosts the 33rd global showcase from 26 July to 11 August, and it is evident that AI is just beginning its revolution in sports. Despite many sceptics, this article demystifies the agenda and highlights the advantages and disadvantages that could significantly influence future developments.
The integration of AI into the Olympics not only seeks to improve the efficiency and accuracy of event management but also aims to elevate the overall quality of the competition. By leveraging advanced technologies, the IOC hopes to create a more engaging and fair experience for athletes, coaches, and fans alike. This initiative marks a significant step forward in the modernisation of the Olympics, ensuring that it remains the premier sporting event in an increasingly digital world.
Injury prevention, motion analysis, and health advice for athletes
Among the many aspects AI will address in the future, injury reduction and faster recovery for athletes are likely the most important. These systems will help identify various weaknesses and strengths, aiding coaches in better preparing their competitors for crucial matches.
Cameras will predominantly cover the fields and provide data during matches, which is crucial for athletes’ endurance. Interestingly, for some analyses, experts will need nothing more than a smartphone.
AI’s role in injury prevention extends beyond immediate physical health, as it also contributes to long-term athlete welfare. By monitoring training loads and biomechanical patterns, AI can alert coaches and medical teams to potential overuse injuries before they become serious. This proactive approach helps maintain peak performance levels while reducing downtime due to injuries, ultimately extending athletes’ careers and enhancing their overall well-being.
Event organisation to ensure adequate rest for athletes
Schedules at major competitions often change due to weather issues or logistical errors. One of the goals of the Olympic AI agenda is to facilitate event preparation months in advance for seamless operation. These systems can anticipate potential problems before the competition starts, minimising errors.
AI can also assist in optimising transportation schedules, accommodation arrangements, and training facilities, ensuring that athletes have the best possible conditions for preparation and recovery. By automating these logistical aspects, the IOC can focus more on the athletes’ needs, reducing stress and allowing them to concentrate fully on their performance. This holistic approach to event management aims to create a more supportive environment for all participants.
Enhancing fan engagement
Sport is played for the fans, so they must not be excluded from this revolutionary process. The Olympic AI agenda aims to give fans a more significant role than ever through personalised content, live statistics, and other features via official apps, enhancing their enjoyment of their favourite competitors’ matches.
Recent research indicates that over 55 per cent of fans support the AI agenda, believing it will greatly improve the development of sports and competition quality.
Additionally, AI can personalise fan experiences by offering customised viewing options and interactive features. Fans could receive tailored content based on their preferences, including highlight reels, player statistics, and behind-the-scenes insights. By integrating social media and real-time feedback, the AI-driven platforms can create a more immersive and engaging experience, making the fans feel more connected to the action and their favourite athletes.
Helping the referees during competition
VAR was introduced in football a few years ago, reducing errors during matches. The Olympic AI agenda will similarly improve assistance to referees in other sports. Special emphasis is placed on gymnastics, where movements will be analysed in minute detail, providing almost perfect analysis to referees for decision-making.
Numerous obstacles will undoubtedly arise before the system reaches optimal condition, but it will simplify the work of referees, fans, and especially competitors, explaining the reasons for decisions in the given moment.
AI’s involvement in officiating also includes the potential to standardise and improve the accuracy of scoring systems across various sports. By reducing human error and bias, AI can ensure that all athletes are judged fairly and consistently, enhancing the integrity of the competition. This technological advancement is particularly crucial in sports with subjective scoring elements, where even minor discrepancies can significantly impact the outcomes.
Live event broadcasting and tracking
Fans often miss something interesting during broadcasts. AI will play a crucial role, making it easier for fans to review key moments as competitions unfold. AI commentators are increasingly mentioned for following less popular sports, gathering data, and providing more information to fans who previously struggled to keep up with the Olympic Games’ pace. Multi-language broadcast options and clear analysis will enhance the overall experience, starting from Paris, through Los Angeles 2028, Brisbane 2032, and beyond.
The integration of AI in broadcasting can also improve the accessibility of Olympic events. Enhanced captioning, audio descriptions, and real-time translations can make the games more inclusive for a global audience. AI-driven analytics can provide deeper insights into the events, helping fans understand complex strategies and techniques, thus broadening the appeal of various sports and attracting new audiences.
AI’s role in security extends beyond cyber threats. It includes monitoring physical security by analysing crowd behaviour, identifying potential safety hazards, and ensuring swift responses to any incidents. These comprehensive security measures aim to create a safe and secure environment, allowing athletes to focus on their performance without concerns about their safety or privacy.
What can we expect?
Given AI’s integral role in recent years, it is hard to believe it will not permeate all aspects, including sports. From athlete injury prevention to logistical solutions aiming to reduce waste, resource consumption, and other key factors for better-organised Games, AI will play a significant role in future major events. Additionally, with the primary goal of maintaining peace and stability for both athletes and fans, this agenda has full support from its developers. Paris 2024 serves as a general rehearsal for what lies ahead, and the outcome will be known once the last medals are awarded on 11 August.
The success of the AI agenda in Paris will likely set the stage for future advancements and innovations in subsequent Olympic Games. As AI technologies evolve, they will continue to refine and enhance various aspects of the Games, ensuring they remain at the top of global sports events. The potential for AI to revolutionise the Olympics is vast, promising a more efficient, engaging, and fair competition for everyone involved.
Oxford Dynamics, based in Harwell, Oxfordshire, is developing a robot named Strider to operate in hazardous environments, such as chemical, biological, or nuclear incidents. The company has secured a £1m contract with the Ministry of Defence to design and supply this advanced robot by September.
Strider is equipped to handle tasks that are dangerous for humans, like retrieving contaminated objects and performing semi-autonomous activities. The robot is designed to navigate difficult terrains using infra-red, radar, and lidar systems, making it highly versatile in various scenarios, including those similar to the Novichok attack in Salisbury.
Mike Lawton, a director at Oxford Dynamics, envisions building thousands of Strider robots to benefit global safety. He emphasizes the importance of deploying machines instead of humans in life-threatening situations. The company also plans to enhance Strider with AVIS AI software, inspired by JARVIS from the Iron Man films, to further improve its capabilities.
Founder Shefali Sharma sees potential for adapting the technology to submarines and fighter jets, aiming to get these innovations into the hands of those who need them most. The initiative has been praised by Defra, highlighting the rapid progress from concept to a highly capable platform.
Alliant Energy has secured several power supply agreements with data centres in Iowa and Wisconsin, as confirmed during a recent post-earnings call. The rise in popularity of AI tools like OpenAI’s ChatGPT has spurred the demand for high-performance data centres, necessitating substantial electricity to process large volumes of data.
The company has been actively working to attract new customers in both states, successfully signing multiple deals with data centres. These agreements highlight Alliant Energy’s strategic efforts to expand its customer base amidst the growing data demands driven by advanced AI technologies.
Despite these new deals, Alliant Energy reported a decline in second-quarter profit, impacted by a settlement agreement related to its Interstate Power and Light unit’s retail electric rate review. This led to a pre-tax non-cash charge of $60 million in the second quarter.
The company’s quarterly adjusted profit for its utilities and corporate services segment fell by 13.8%, equating to 56 cents per share, compared to the previous year. Overall profit for the quarter ended June 30 was $87 million, down from $160 million a year earlier.
According to the New York Times, Meta is negotiating with actors such as Awkwafina, Judi Dench and influencers to use their voices for its MetaAI digital assistant. The social media giant is also in talks with comedian Keegan-Michael Key and other celebrities, with Hollywood’s top talent agencies involved in the negotiations.
On Wednesday, Meta announced its commitment to significant spending on AI infrastructure. Like many tech companies, Meta has invested billions in its data centres to leverage the generative AI boom.
While it’s unclear which celebrities might finalise deals, reports suggest Meta could pay millions in fees to secure their voices. Meta did not comment on these discussions.
AI-generated music faces strong opposition from musicians and major record labels over concerns about copyright infringement. Grammy-nominated artist Tift Merritt and other prominent musicians have criticised AI music platforms like Udio for producing imitations of their work without permission. Merritt argues that these AI-generated songs are not transformative but amount to theft, harming creativity and human artists.
Major record labels, including Sony, Universal, and Warner Music, have taken legal action against AI companies like Udio and Suno. These lawsuits claim that the companies have used copyrighted recordings to train their systems without proper authorisation, thus creating unfair competition by flooding the market with cheap imitations. The labels argue that such practices drain revenue from real artists and violate copyright laws.
The AI companies defend their technology, asserting that their systems do not infringe on copyrights and that their practices fall under ‘fair use.’ They liken the backlash to past industry fears over new technologies like synthesisers and drum machines. However, the record labels maintain that AI systems misuse copyrighted material to mimic famous artists without appropriate licenses, including Mariah Carey and Bruce Springsteen.
Why does this matter?
These legal battles echo other high-profile copyright cases involving generative AI, such as those against chatbots like OpenAI’s ChatGPT. The outcome of these cases could set significant precedents for using AI in creative industries, with courts needing to address whether AI’s use of copyrighted material constitutes fair use or infringement.
