MIT researchers have used generative AI to design novel antibiotics targeting drug-resistant bacteria such as gonorrhea and MRSA. Laboratory tests show the compounds kill bacteria without harming human cells, marking a potential breakthrough in antibiotic development.
The AI system analysed over 36 million possible compounds, generating entirely new molecules with mechanisms that bypass existing resistance. Unlike traditional methods, this approach enables faster discovery, reducing drug development timelines from years to months.
Drug resistance is a growing global threat, with the World Health Organisation predicting 10 million annual deaths by 2050 if unchecked. MIT’s AI bypasses resistance, clearing infections in lab and animal tests with minimal toxicity.
Beyond antibiotics, this achievement highlights the broader potential of AI in pharmaceutical research. Smaller biotech firms could leverage AI for rapid drug design, reducing costs and opening new pathways for addressing urgent medical challenges.
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Chinese physicist Pan Jianwei’s team created the world’s largest atom array, arranging over 2,000 rubidium atoms for quantum computing. The breakthrough at the University of Science and Technology of China could enable atom-based quantum computers to scale to tens of thousands of qubits.
Researchers used AI and optical tweezers to position all atoms simultaneously, completing the array in 60 milliseconds. The system achieved 99.97 percent accuracy for single-qubit operations and 99.5 percent for two-qubit operations, with 99.92 percent accuracy in qubit state detection.
Atom-based quantum computing is more promising for its stability and control than superconducting circuits or trapped ions. Until now, arrays were limited to a few hundred atoms, as moving each into position individually was slow and challenging.
Future work aims to expand array sizes further using stronger lasers and faster light modulators. Researchers hope that perfectly arranging tens of thousands of atoms leads to fully reliable and scalable quantum computers.
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Igor Babuschkin, cofounder of Elon Musk’s AI startup xAI, has announced his departure to launch an investment firm dedicated to AI safety research. Musk created xAI in 2023 to rival Big Tech, criticising industry leaders for weak safety standards and excessive censorship.
Babuschkin revealed his new venture, Babuschkin Ventures, will fund AI safety research and startups developing responsible AI tools. Before leaving, he oversaw engineering across infrastructure, product, and applied AI projects, and built core systems for training and managing models.
His exit follows that of xAI’s legal chief, Robert Keele, earlier this month, highlighting the company’s churn amid intense competition between OpenAI, Google, and Anthropic. The big players are investing heavily in developing and deploying advanced AI systems.
Babuschkin, a former researcher at Google DeepMind and OpenAI, recalled the early scramble at xAI to set up infrastructure and models, calling it a period of rapid, foundational development. He said he had created many core tools that the startup still relies on.
Last month, X CEO Linda Yaccarino also resigned, months after Musk folded the social media platform into xAI. The company’s leadership changes come as the global AI race accelerates.
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Anthropic has outlined a multi-layered safety plan for Claude, aiming to keep it useful while preventing misuse. Its Safeguards team blends policy experts, engineers, and threat analysts to anticipate and counter risks.
The Usage Policy establishes clear guidelines for sensitive areas, including elections, finance, and child safety. Guided by the Unified Harm Framework, the team assesses potential physical, psychological, and societal harms, utilizing external experts for stress tests.
During the 2024 US elections, a TurboVote banner was added after detecting outdated voting info, ensuring users saw only accurate, non-partisan updates.
Safety is built into development, with guardrails to block illegal or malicious requests. Partnerships like ThroughLine help Claude handle sensitive topics, such as mental health, with care rather than avoidance or refusal.
Before launch, Claude undergoes safety, risk, and bias evaluations with government and industry partners. Once live, classifiers scan for violations in real time, while analysts track patterns of coordinated misuse.
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Google has announced a $9 billion investment in Oklahoma over the next two years to expand cloud and AI infrastructure.
The funds will support a new data centre campus in Stillwater and an expansion of the existing facility in Pryor, forming part of a broader $1 billion commitment to American education and competitiveness.
The announcement was made alongside Governor Kevin Stitt, Alphabet and Google executives, and community leaders.
Alongside the infrastructure projects, Google funds education and workforce initiatives with the University of Oklahoma and Oklahoma State University through the Google AI for Education Accelerator.
Students will gain no-cost access to Career Certificates and AI training courses, helping them acquire critical AI and job-ready skills instead of relying on standard curricula.
Additional funding will support ALLIANCE’s electrical training to expand Oklahoma’s electrical workforce by 135%, creating the talent needed to power AI-driven energy infrastructure.
Google described the investment as part of an ‘extraordinary time for American innovation’ and a step towards maintaining US leadership in AI.
The move also addresses national security concerns, ensuring the country has the infrastructure and expertise to compete with domestic rivals like OpenAI and Anthropic, as well as international competitors such as China’s DeepSeek.
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At the Emkay Confluence in Mumbai, Chief Economic Adviser V. Anantha Nageswaran emphasised that while trade-related concerns remain significant, they must not obscure the urgent need for India to boost its AI and semiconductor sectors.
He pointed to AI’s transformative economic potential and strategic importance, warning that India must act decisively to remain competitive as the United States and China advance aggressively in these domains.
By focusing on energy transition, energy security, and enhanced collaboration across sectors, Nageswaran argued that India can strengthen its innovation capacity and technological self-reliance.
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Prime Minister Olzhas Bektenov established a digital transformation group, or digital headquarters, to advance AI integration across Kazakhstan, following President Tokayev’s directives on 11 August 2025.
The group includes senior officials, such as the deputy prime minister, the head of strategic planning, the minister of digital development, innovation, and aerospace industry, and the presidential digitalisation advisor. The group is tasked with implementing nine priority areas outlined by the president.
These span AI deployment in the economy, public administration, and healthcare; digital strategy development; IT architecture modernisation; cybersecurity; support for IT startups; the national QazTech platform; and innovative city initiatives.
A significant plan component involves crafting a roadmap with the Samruk Kazyna Sovereign Wealth Fund to embed AI in production and boost labour productivity. AI solutions are expected to improve diagnostics, personalise treatment, enable continuous patient monitoring, and streamline workflows in healthcare. Startups will gain access to the Ministry of Health infrastructure and integration into a unified medical database.
Consolidating government communication via the Aitu national messenger, IT modernisation, and strengthened cybersecurity aims to create a seamless, safe digital environment for citizens. The emphasis is swift collaboration to address AI integration challenges across all sectors.
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According to Science and Technology Daily, Chinese researchers have reported a breakthrough in quantum drug discovery using edge encoding. Origin Quantum, USTC, and the Hefei AI Institute built a quantum-embedded graph neural network (GNN) to predict drug-molecule properties.
In drug development, graph neural networks model molecules as atoms and bonds. Classical and some quantum approaches handle atoms well but struggle with bonds. The gap limits accuracy and screening speed.
The team from China introduced quantum edge and node embeddings to process bonds and atoms simultaneously at the quantum level. The quantum-embedded GNN unifies both signals in one pass. Results show sharper predictions for the properties of candidate drugs.
Validation on the Origin Wukong quantum computer indicates stable performance despite today’s noisy hardware. Benchmarking suggests efficiency gains for molecular screening pipelines. Researchers say the approach is production-oriented as devices scale.
Findings appear in the Journal of Chemical Information and Modelling. Collaboration highlights China’s push to integrate quantum computing with biopharmaceutical research and development. More exhaustive testing on larger qubit counts is anticipated.
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A recent survey by the Association of Accounting Technicians (AAT) finds that two in five people would consider a career in accountancy if AI could handle routine tasks. The research suggests automation may improve the profession’s appeal by shifting the focus from admin to strategic support.
Among current accountants, four in five agree that AI tools have made their roles easier by lightening administrative burdens, while 80% say it enables more problem-solving and advisory work. AI will enhance efficiency and accuracy, and allow finance professionals to concentrate on impactful tasks.
The survey reveals 42% of those who have worked in accounting say AI tools have been genuinely valuable; this rises to 55% for 25- to 34-year-olds. Most also support upskilling, with nearly 80% interested in developing AI and machine learning skills as part of workplace training.
Claire Bennison of AAT stresses that AI is not here to replace accountants but to empower them. She argues that building an AI-savvy workforce is essential in meeting skills shortages and modernising the finance profession.
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OpenAI has introduced updates to its GPT-5 model following user feedback. CEO Sam Altman announced that users can now choose between Auto, Fast, and Thinking modes, along with an updated personality for the AI.
The changes aim to enhance user experience by providing greater control over the model’s behaviour. Altman noted that while more users work with reasoning-focused models, they still represent a relatively small portion of the total user base.
The update reflects OpenAI’s ongoing commitment to tailoring AI interactions based on user preferences and feedback, ensuring the flagship model remains adaptable and responsive to diverse needs.
GPT-5 faced a rocky launch as users found it surprisingly less capable than GPT-4o, due to a malfunctioning real-time router that misrouted queries. Sam Altman acknowledged the issue, restoring GPT-4o access and doubling rate limits for Plus subscribers.
The episode has also sparked debate in the AI community about balancing innovation with emotional resonance, as some users note GPT-5’s colder tone despite its safer, more aligned behaviour.
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