US federal prosecutors are ramping up efforts to tackle the use of AI tools in creating child sexual abuse images, as they fear the technology could lead to a rise in illegal content. The Justice Department has already pursued two cases this year against individuals accused of using generative AI to produce explicit images of minors. James Silver, chief of the Department’s Computer Crime and Intellectual Property Section, anticipates more cases, cautioning against the normalisation of AI-generated abuse material.
Child safety advocates and prosecutors worry that AI systems can alter ordinary photos of children to produce abusive content, making it more challenging to identify and protect actual victims. The National Center for Missing and Exploited Children reports approximately 450 cases each month involving AI-generated abuse. While this number is small compared to the millions of online child exploitation reports received, it represents a concerning trend in the misuse of technology.
The legal framework is still evolving regarding cases involving AI-generated abuse, particularly when identifiable children are not depicted. Prosecutors are resorting to obscenity charges when traditional child pornography laws do not apply. This is evident in the case of Steven Anderegg, accused of using Stable Diffusion to create explicit images. Similarly, US Army soldier Seth Herrera faces child pornography charges for allegedly using AI chatbots to alter innocent photos into abusive content. Both defendants have pleaded not guilty.
Nonprofit groups like Thorn and All Tech Is Human are working with major tech companies, including Google, Amazon, Meta, OpenAI, and Stability AI, to prevent AI models from generating abusive content and to monitor their platforms. Thorn’s vice president, Rebecca Portnoff, emphasised that the issue is not just a future risk but a current problem, urging action during this critical period to prevent its escalation.
The authors make several points relevant to the global AI discussions. First, as AI becomes integral to the global economy, warning echo of the looming threat of concentrated corporate control, which risks stifling innovation, compromising consumer privacy, and undermining democratic values. To combat it, the authors advocate for a diverse AI market that includes public, private, and non-profit stakeholders to ensure the technology’s benefits are widely distributed.
In "Stopping Big Tech from Becoming Big AI" we lay out a series of detailed, practical measures to check rising market concentration and keep AI open for all 🧵 pic.twitter.com/gaHjwHwLYL
Second, the report mentions monopolistic risks, through tactics such as exclusive partnerships and control over computing power that allow dominant firms to consolidate power, restricting competition and innovation. Despite often being unseen by consumers, these practices could centralise AI development and inhibit market diversity. As an action point, the authors call on governments to act swiftly using existing regulatory tools, such as blocking mergers and enforcing ex-ante competition policies, to dismantle these barriers and impose fair access rules on essential AI resources.
Finally, international cooperation is one of the key points, particularly the importance of recognising the global nature of AI development. Authors warn against repeating past mistakes of digital market dominance, emphasising the need for a unified approach to AI regulation. Through fostering competition, the report asserts that AI can deliver broader societal benefits, prioritising innovation and privacy over profit maximisation and surveillance.
Why does it matter?
The global community sees the current moment as a pivotal chance to shape AI’s future for the collective good, urging immediate regulatory intervention. Echoing this approach, this report aims to ensure that AI remains a competitive field characterised by transparency and fairness, safeguarding a digital economy that benefits all stakeholders equally.
Alphabet has transferred the Gemini app team to DeepMind, streamlining operations to accelerate progress in generative AI. The decision aims to foster quicker deployment and seamless collaboration across its AI platforms.
Sundar Pichai, Google’s CEO, highlighted that the change would enhance feedback cycles and improve the rollout of models within the Gemini app. Gemini represents Google’s most advanced AI technology, with the app offering direct access to the latest developments.
Sissie Hsiao, who previously led the Gemini app team, will now report to Demis Hassabis, CEO of Google DeepMind. This realignment reflects the company’s broader efforts to strengthen its generative AI capabilities.
Google also reshuffled senior leadership, appointing Prabhakar Raghavan as chief technologist. His former role in search and information management will be taken over by Nick Fox, aligning the company’s AI product strategy under new leadership.
Mistral, a French AI startup, has launched its first generative AI models, ‘Les Ministraux,’ designed to run on edge devices like laptops and mobile phones. The models, Ministral 3B and Ministral 8B, offer versatile applications such as on-device translation and autonomous robotics, catering to privacy-focused, low-latency scenarios.
Both models can process 128,000 tokens, roughly the length of a 50-page book. While Ministral 8B is available for research purposes, commercial licences for self-deployment are being offered directly by Mistral. Developers can also access the models through Mistral’s cloud platform, La Platforme.
Smaller AI models are increasingly in demand due to their cost-effectiveness and efficiency. Mistral claims that its Ministral models outperform competitors like Llama and Gemma across several benchmarks, offering strong instruction-following and problem-solving capabilities.
Paris-based Mistral, which has raised $640 million in venture capital, continues to expand its AI portfolio. The company has introduced services such as developer testing and model fine-tuning, positioning itself as a competitor to major players like OpenAI and Anthropic.
Photonic chip startup Lightmatter has raised $400 million in a Series D funding round led by T. Rowe Price, valuing the company at $4.4 billion. This funding boost comes amid surging demand for more efficient data center infrastructure due to the rise of artificial intelligence technologies like ChatGPT. With backing from investors such as Fidelity and Alphabet’s GV, Lightmatter plans to use the capital to produce and deploy its innovative chips and expand its workforce across the US and Canada.
The Mountain View-based company, founded in 2017, specialises in using silicon photonics to build faster and more energy-efficient chips, a crucial technology for AI and cloud computing. Co-founder and CEO Nick Harris indicated that this could be the company’s last private funding round, with plans to go public in the near future. He emphasised that photonic chips are the future of high-performance computing, which is why Lightmatter has secured large deals with major tech players, though the company has not disclosed specific clients.
With the potential to work across platforms like Nvidia, Intel, and AMD, Lightmatter’s technology aims to significantly increase AI cluster bandwidth while lowering energy consumption. Its first large AI clusters are expected to be operational next year as the company prepares for an initial public offering.
Governments around the world are scrambling to establish protections surrounding AI development and use, according to Doreen Bogdan-Martin, Secretary-General of the International Telecommunication Union (ITU). Speaking at a regulatory conference, she noted that only 15% of ITU’s 194 member states have begun developing policies in this area, leaving the vast majority without regulatory frameworks for AI.
Martin pointed out that many countries are eager to join discussions and learn from others that have advanced in AI regulation. She highlighted India‘s success in building a digital public infrastructure, particularly its unified payments interface and Aadhaar digital identity system, calling the country a global leader in this space. India’s fast 5G network has also positioned it as a key player in the digital economy.
Reflecting on past regulatory efforts to improve internet access, Martin explained that regulators today face a more complex landscape. AI’s integration with telecoms is a particular area of focus, as policymakers consider how to regulate in a world where digital infrastructure is increasingly interconnected.
Martin also stressed the growing challenges posed by cyberattacks, which are rising 80% year on year, and the risks posed by AI-driven deepfakes and disinformation. Strengthening network resilience and ensuring global participation in the digital economy remain critical concerns.
Achieving human-level AI may be at least a decade away, according to Meta’s AI scientist, Yann LeCun. Current AI systems, like large language models, fall short of true reasoning, memory, and planning, even though companies like OpenAI market their technologies with terms like ‘memory’ and ‘thinking’. LeCun cautions against the hype, saying these systems lack the deeper understanding required for complex human tasks.
LeCun argues that the limitations stem from how these AI models function. LLMs predict words, while image and video models predict pixels, making them capable of only single or two-dimensional predictions. In contrast, humans operate in a three-dimensional world, able to plan and adapt intuitively. Even the most advanced AI struggles with everyday actions, such as cleaning a room or driving a car, tasks children and teenagers can learn with ease.
The key to more advanced AI, according to LeCun, lies in ‘world models’ – systems capable of perceiving and predicting outcomes within a three-dimensional environment. These models would allow AI to form action plans without trial and error, similar to how humans quickly solve problems by envisioning the results of their actions. However, building these systems requires massive computational power, driving cloud providers to partner with AI companies.
FAIR, Meta’s research arm, has shifted its focus towards developing world models and objective-driven AI. Other labs are also pursuing this approach, with researchers such as Fei-Fei Li raising significant funding to explore the potential of world models. Despite growing interest, LeCun emphasises that significant technical challenges remain, and achieving human-level AI will likely take many years, if not a full decade.
With the US facing a growing shortage of electricians, Treehouse, a startup, is using AI to help make installations of electric vehicle (EV) chargers, heat pumps, and other tech more efficient and affordable. As the demand for renewable energy and electrification surges, Treehouse has developed AI models to predict job times, materials needed, and to eliminate unnecessary site visits, which typically slow down the process. By gathering data and asking customers key questions, Treehouse can streamline quoting and installation processes, especially for simpler jobs like EV chargers.
Treehouse uses its AI-driven platform to design installations and assist in permitting, often completing jobs with minimal visits from electricians. For more complex installations, like heat pumps, the company may require additional photos or virtual visits. Treehouse works in 40 states, hiring independent electricians for many of the jobs, and plans to expand its operations across all 50 states by the end of the year. With a recent $16 million Series A funding round, the company aims to improve its AI tools and grow its team.
Founder and CEO Eric Owski believes the electrification trend will continue to reshape how consumers think about home energy, with EV chargers being just the starting point. Treehouse’s partnerships with companies like CarMax and ChargePoint also help boost its reach as it tackles the ongoing electrician shortage.
The US Department of Justice (DOJ) has released a significant Statement of Interest, urging scrutiny of surveys and information exchanges managed by trade associations. The DOJ expressed concerns that such exchanges may create unique risks to competition, particularly when competitors share sensitive information exclusively among themselves.
According to the DOJ, antitrust laws will evaluate the context of any information exchange to determine its potential impact on competition. Sharing competitively sensitive information could disproportionately benefit participating companies at the expense of consumers, workers, and other stakeholders. The department noted that advancements in AI technology have intensified these concerns, allowing large amounts of detailed information to be exchanged quickly, potentially heightening the risk of anticompetitive behaviour.
This guidance follows the DOJ’s withdrawal of long-standing rules that established “safety zones” for information exchanges, which previously indicated that certain types of sharing were presumed lawful. By retracting this guidance, the DOJ signals a shift toward a more cautious, case-by-case approach, urging businesses to prioritise proactive risk management.
The DOJ’s statement, made in relation to an antitrust case in the pork industry, has wider implications for various sectors, including real estate. It highlights the need for organisations, such as Multiple Listing Services (MLS) and trade associations, to evaluate their practices and avoid environments that could lead to price-fixing or other anticompetitive behaviours. The DOJ encourages trade association executives to review their information-sharing protocols, educate members on legal risks, and monitor practices to ensure compliance with antitrust laws.
Japan’s largest annual electronics event opened alongside a mobility show, marking the first joint trade fair of its kind. The collaboration reflects the increasing convergence of technology and automotive industries, especially as vehicles become more autonomous and connected.
The trade show, hosted by the Japan Electronics and Information Technology Industries Association (JEITA) and Japan Automobile Manufacturers Association (JAMA), aims to promote cross-industry innovation. AI emerged as a core theme, with around half of the 800 tech exhibitors presenting AI-driven products and solutions.
Toyota Motor showcased a portable hydrogen tank capable of powering electric generators during disasters, promoting hydrogen as a sustainable energy source. Panasonic highlighted its perovskite solar cells, which can be installed on car windows to enhance power efficiency for electric vehicles, while Sony demonstrated a safety system that uses image sensors to detect driver fatigue.
NEC presented an AI-powered service capable of summarising movies or creating accident reports from dashcam footage, offering applications in various fields. TDK introduced a brain-inspired semiconductor chip that reduces AI electricity consumption to one-hundredth of current levels. The fair runs until Friday at Chiba’s Makuhari Messe, with free entrance for online registrants.
