Elon Musk has echoed concerns from AI researchers that the industry is running out of new, real-world data to train advanced models. Speaking during a livestream with Stagwell’s Mark Penn, Musk noted that AI systems have already processed most of the available human knowledge. He described this data plateau as having been reached last year.
To address the issue, AI developers are increasingly turning to synthetic data, information generated by the AI itself, to continue training models. Musk argued that self-generated data will allow AI systems to improve through self-learning, with major players like Microsoft, Google, and Meta already incorporating this approach in their AI models.
While synthetic data offers cost-saving advantages, it also poses risks. Some experts warn it could cause “model collapse,” reducing creativity and reinforcing biases if the AI reproduces flawed patterns from earlier training data. As the AI sector pivots towards self-generated training material, the challenge lies in balancing innovation with reliability.
Serve Robotics, backed by Nvidia and Uber, has secured $80 million through a direct stock offering to institutional investors. The funding will support the expansion of its autonomous delivery robot fleet, with plans to scale from 100 robots in Los Angeles to 2,000 across multiple US cities by the end of 2025. CFO Brian Read stated that the investment is intended for long-term growth rather than short-term expenditure, positioning the company for sustained financial stability beyond 2026.
The fresh capital follows $86 million raised in December 2024, bringing Serve’s total funding to over $247 million in the past year. The company aims to use its reserves to self-finance equipment investments, reducing reliance on external financing and improving cash flow. Read highlighted that full ownership of the robots would provide greater financial flexibility and lower operational costs as the fleet expands.
Currently, Serve operates around 100 robots in Los Angeles, delivering for Uber Eats and 7-Eleven. A trial in Dallas, launched in partnership with Wing, is exploring hybrid drone and sidewalk robot deliveries. The company plans to deploy 250 additional robots in Los Angeles in early 2025, with the goal of achieving cash-flow positivity once the 2,000-robot fleet reaches full utilisation.
Microsoft will invest $3 billion to expand AI and cloud-computing infrastructure in India, CEO Satya Nadella announced during a conference in Bengaluru. The investment, the company’s largest expansion in the country, aims to strengthen its Azure cloud services and AI capabilities. Nadella also revealed plans to train 10 million people in AI by 2030, building on an earlier commitment to provide AI skilling opportunities for two million individuals by 2025, with a focus on smaller cities and rural areas.
India’s growing importance as a tech hub has attracted interest from major US technology firms, with recent visits from Nvidia’s Jensen Huang and Meta’s chief AI scientist Yann LeCun. Nadella met Prime Minister Narendra Modi to discuss technology, innovation, and Microsoft‘s ambitious plans for expansion in the country. India’s vast population and affordable internet access make it a key market for AI-driven growth.
Microsoft is making significant global investments in AI and cloud infrastructure, committing around $80 billion in fiscal 2025. More than half of that will be directed towards US data centers to support AI model training and cloud-based applications. With India positioned as a strategic market, Microsoft’s latest investment underscores the country’s growing role in the global AI ecosystem.
China has introduced a groundbreaking addition to its law enforcement toolkit – the Rotunbot RT-G, a spherical robot designed to aid police in high-speed chases and challenging terrains. Developed by Logon Technology, this 276-pound robotic marvel can travel up to 22 mph on land and water, navigate mud and rivers, and even withstand drops from ledges. Its rapid acceleration and amphibious capabilities make it a unique asset for pursuit scenarios.
Equipped with advanced technology, the RT-G boasts GPS for precise navigation, cameras, ultrasonic sensors, and systems for tracking and avoiding obstacles. Gyroscopic self-stabilisation ensures smooth operation, while a suite of non-lethal tools—including tear gas dispensers, net shooters, and acoustic crowd dispersal devices—enables it to handle diverse law enforcement tasks humanely and effectively.
The RT-G is already used in Wenzhou, Zhejiang province of China, where it assists police in commercial zones. While its real-world performance shows promise, limitations such as instability during turns and difficulty navigating stairs reveal areas for improvement. Despite these challenges, the Rotunbot RT-G represents a significant leap in robotic policing technology, blending innovation with practicality.
AI is revolutionising the legal field, offering solutions to improve fairness and reduce costs in the justice system. Tools powered by AI are being used to streamline tasks like analysing evidence, drafting contracts, and preparing cases. Organisations like the Westway Trust in London are adopting AI to assist clients with complex disputes, such as benefits appeals and housing issues. These tools save hours of work, enabling paralegals to focus on providing better support.
The technology has sparked excitement and debate among legal professionals. AI models are being developed to help barristers identify inconsistencies in real-time court transcripts and assist judges with evidence analysis. Advocates argue that AI could make justice more accessible, while reducing the burden on legal practitioners and cutting costs for clients. However, concerns about accuracy and bias persist, with experts emphasising the importance of human oversight.
Sir Geoffrey Vos, Master of the Rolls, underscores the need for AI to complement, not replace, human judges. Guidelines stress transparency in AI use and the responsibility of lawyers to verify outputs. While tools like ChatGPT can provide general advice, professionals caution against relying on non-specialised AI for legal matters. Experts believe that AI will play a crucial role in addressing the fairness gap in the justice system without compromising the rule of law.
Miles Laflin, a Bedfordshire-based pool cleaner known as ‘The Pool Guy’, has amassed over 22 million followers across social media platforms for his visually satisfying videos of pool cleaning. Despite his fame, the 34-year-old continues his day job, crediting it with keeping him grounded. Laflin has been in the pool cleaning business for over a decade and began sharing his work on TikTok, where a single video has attracted over 170 million views.
His viral content has significantly boosted his business, with 90% of his work coming from followers who discover him online. Laflin’s success led to him winning the high-quality content creator of the year title at the inaugural UK and Ireland TikTok Awards. He encourages others to share content about their jobs, emphasising that social media offers opportunities for brand deals, global travel, and personal transformation.
Laflin continues to balance his viral fame with his pool cleaning business, a testament to his passion for the trade. He believes there is an audience for every profession, urging aspiring content creators to showcase their unique skills online.
The automation industry is evolving beyond Robotic Process Automation (RPA) to embrace multi-agentic AI systems capable of autonomous decision-making. Companies like Automation Anywhere are at the forefront, introducing AI Agent Studio to help enterprises streamline operations across finance, HR, IT, and customer service. These agents accelerate workflows, reduce costs, and enhance operational efficiency by up to 90%.
Automation Anywhere executives highlight how these advanced AI agents surpass earlier systems by integrating retrieval-augmented generation (RAG) with decision-making capabilities. Unlike static models, these agents learn from user interactions, ensuring adaptability and accuracy. Their blend of RAG and AI offers enterprises scalable, secure, and flexible solutions tailored to specific needs.
The shift from RPA to Agentic Process Automation (APA) marks a milestone, enabling automation of complex processes while fostering innovation and redefining job roles. With applications spanning healthcare, finance, retail, and manufacturing, AI agents are poised to disrupt industries and drive significant growth.
Instacart has joined Uber in a legal challenge against a new Seattle ordinance regulating how app-based workers can be deactivated. The law, set to take effect in January, requires companies to provide gig workers with a 14-day notice of deactivation, base decisions on reasonable policies, and allow human review of all deactivations.
Seattle officials describe the legislation as a landmark move to ensure worker rights in the gig economy. Advocacy groups support the law, arguing that it addresses unfair deactivations and offers greater job security for app-based workers.
Instacart and Uber, however, claim the ordinance infringes on constitutional rights, federal laws, and operational safety. This lawsuit is part of broader disputes between tech companies and cities over labour regulations in the gig economy. Seattle has pledged to defend its policies, emphasising its commitment to protecting workers in modern app-driven industries.
Kyoto University and construction firm Kajima Corp are collaborating on a groundbreaking project to develop a lunar habitat, ‘Neo Lunar Glass,’ capable of generating artificial gravity through rotation. The structure, intended to address the harmful effects of microgravity on the human body, is designed to create Earth-like living conditions on the moon.
The habitat will be a 200-metre-wide, 400-metre-tall paraboloid structure, accommodating up to 10,000 residents. Researchers plan to construct a ground-based prototype by the 2030s, using models and simulations to refine the technology.
The project aims to revolutionise lunar colonisation and human survivability in space, with a scale model already unveiled and early simulations demonstrating artificial gravity’s feasibility.
If AI was the buzzword for 2023 and 2024, quantum computing looks set to claim the spotlight in the years ahead. Despite growing interest, much remains unknown about this transformative technology, even as leading companies explore its immense potential.
Quantum computing and AI stand as two revolutionary technologies, each with distinct principles and goals. Quantum systems operate on the principles of quantum mechanics, using qubits capable of existing in multiple states simultaneously due to superposition. Such systems can address problems far beyond the reach of classical computers, including molecular simulations for medical research and complex optimisation challenges.
AI and quantum computing intersect in areas like machine learning, though AI still depends on classical computing infrastructure. Significant hurdles remain for quantum technology, including qubit errors and scalability. The extreme sensitivity of qubits to external factors, such as vibrations and temperature, complicates their control.
Experts suggest quantum computers could become practical within 10 to 20 years. Classical computers are unlikely to be replaced, as quantum systems will primarily focus on solving tasks beyond classical capabilities. Leading companies are working to shorten development timelines, with advancements poised to transform the way technology is utilised.
Huge investments in quantum computing
Investments in quantum computing have reached record levels, with start-ups raising $1.5 billion across 50 funding rounds in 2024. Figure like this one nearly doubles the $785 million raised the previous year, setting a new benchmark. The growth in AI is partly driving these investments, as quantum computing promises to handle AI’s significant computational demands more efficiently.
Quantum computing offers unmatched speed and energy efficiency, with some estimates suggesting energy use could be reduced by up to 100 times compared to traditional supercomputers. As the demand for faster, more sustainable computing grows, quantum technologies are emerging as a key solution.
Microsoft and Atom Computing announce breakthrough
In November 2024, Microsoft and Atom Computing achieved a milestone in quantum computing. Their system linked 24 logical qubits using just 80 physical qubits, setting a record in efficiency. This advancement could transform industries like blockchain and cryptography by enabling faster problem-solving and enhancing security protocols.
Despite the challenges of implementing such systems, both companies are aiming to release a 1,000-qubit quantum computer by 2025. The development could accelerate the adoption of quantum technologies across various sectors, paving the way for breakthroughs in areas such as machine learning and materials science.
Overcoming traditional computing’s limitations
Start-ups like BlueQubit are transforming quantum computing into a practical tool for industries. The San Francisco-based company has raised $10 million to launch its Quantum-Software-as-a-Service platform, enabling businesses to use quantum processors and emulators that perform tasks up to 100 times faster than conventional systems.
Industries such as finance and pharmaceuticals are already leveraging quantum optimisation. Specialised algorithms are addressing challenges like financial modelling and drug discovery, showcasing quantum computing’s potential to surpass traditional systems in tackling complex problems.
Google among giants pushing quantum computing
Google has recently introduced its cutting-edge quantum chip, Willow, capable of solving a computational problem in just five minutes. Traditional supercomputers would require approximately 10 septillion years for the same task.
The achievement has sparked discussions about quantum computing’s link to multiverse theories. Hartmut Neven, head of Google’s Quantum AI team, suggested the performance might hint at parallel universes influencing quantum calculations. Willow’s success marks significant advancements in cryptography, material science, and artificial intelligence.
Commercialisation is already underway
Global collaborations are fast-tracking quantum technology’s commercialisation. SDT, a Korean firm, and Finnish start-up SemiQon have signed an agreement to integrate SemiQon’s silicon-based quantum processing units into SDT’s precision measurement systems.
SemiQon’s processors, designed to work with existing semiconductor infrastructure, lower production costs and enhance scalability. These partnerships pave the way for more stable and cost-effective quantum systems, bringing their use closer to mainstream industries.
Quantum technologies aiding mobile networks
Telefonica Germany and AWS are exploring quantum applications in mobile networks. Their pilot project aims to optimise mobile tower placement, improve network security with quantum encryption, and prepare for future 6G networks.
Telefonica’s migration of millions of 5G users to AWS cloud infrastructure demonstrates how combining quantum and cloud technologies can enhance network efficiency. The project highlights the growing impact of quantum computing on telecommunications.
Addressing emerging risks
Chinese researchers at Shanghai University have exposed the potential threats quantum computing poses to existing encryption standards. Using a D-Wave quantum computer, they breached algorithms critical to modern cryptographic systems, including AES-256, commonly used for securing cryptocurrency wallets.
Although current quantum hardware faces environmental and technical limitations, researchers stress the urgent need for quantum-resistant cryptography. New encryption methods are essential to safeguard digital systems against future quantum-based vulnerabilities.
Quantum computing promises revolutionary capabilities but must overcome significant challenges in scaling and stability. Its progress depends on interdisciplinary collaboration in physics, engineering, and economics. While AI thrives on rapid commercial investment, quantum technology requires long-term support to fulfil its transformative potential.
