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AI-Enhanced CRISPR Promises Accelerated Gene Therapy Development, Stanford

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In a groundbreaking advancement poised to revolutionize genetic research, Stanford Medicine scientists have unveiled CRISPR-GPT, an artificial intelligence–powered assistant that fundamentally transforms how gene-editing experiments are designed and conducted. This cutting-edge AI tool operates as a dynamic “copilot,” guiding researchers through the complex landscape of CRISPR-based genome editing, effectively lowering the barrier to entry for novices while accelerating workflows for seasoned scientists. By automating experiment design, analyzing data, and diagnosing potential pitfalls, CRISPR-GPT promises to usher in a new era of rapid therapeutic development and biotechnological innovation.

CRISPR technology itself has already reshaped molecular biology by enabling precise genome editing, with applications ranging from treating genetic disorders to enhancing agricultural traits. Yet, despite its transformative potential, the intricacies of designing accurate, efficient CRISPR experiments remain a significant bottleneck. Researchers often grapple with protracted cycles of trial and error to optimize guide RNA designs, target selections, and off-target risk assessments. CRISPR-GPT addresses this challenge head-on by leveraging an extensive corpus of CRISPR experimental data and scientific discourse accumulated over more than a decade to provide a predictive and interactive design framework.

At the heart of CRISPR-GPT lies a sophisticated natural language processing model trained on eleven years of expert knowledge, including online expert conversations and published literature on CRISPR methodologies. This deep training enables the AI to “think” like an experienced geneticist, parsing user queries articulated in everyday language and generating comprehensive experimental plans. Users communicate their research objectives, gene sequences, and specific constraints through a text-based interface, after which CRISPR-GPT synthesizes tailored strategies for genome editing while preemptively highlighting common experimental pitfalls based on historical patterns.

One notable example illustrating CRISPR-GPT’s efficacy involved undergraduate researcher Yilong Zhou from Tsinghua University. Tasked with activating genes in melanoma cells to investigate immunotherapy resistance, Zhou was able to successfully design his CRISPR activation experiment on a single attempt, a feat that frequently requires multiple iterations even for more experienced scientists. Through an engaging dialogue with the AI, Zhou received detailed explanations at each step, which demystified complex processes and fostered a deeper conceptual understanding, effectively transforming CRISPR-GPT from a mere computational tool into an accessible and patient lab partner.

The system’s versatility is further exemplified by its three distinct operational modes—beginner, expert, and question-answer. In beginner mode, CRISPR-GPT adopts a didactic stance, providing not only procedural recommendations but also detailed reasoning behind each suggestion, making it ideal for students and early-career researchers. Expert mode positions the AI as a peer collaborator, engaging advanced practitioners without excess elaboration. The Q&A function serves as a rapid-response mechanism for addressing specific technical inquiries, streamlining dialogues between scientists and enhancing research efficiency.

CRISPR-GPT also incorporates predictive modeling of off-target editing events, a critical aspect of CRISPR experimentation. Off-target mutations can introduce unintended genetic alterations, potentially leading to erroneous conclusions or harmful side effects in therapeutic contexts. By integrating vast datasets encompassing known off-target propensities and experimental outcomes, the AI can estimate the likelihood and potential consequences of such events, enabling researchers to select guide RNAs with optimized specificity and safety profiles. This capability not only reduces the need for extensive validation rounds but also bolsters the biosecurity and ethical conduct of gene-editing research.

Safety and ethical responsibility are integral to the design of CRISPR-GPT. Recognizing the dual-use nature of gene-editing technologies, the development team embedded safeguards that detect and prevent AI assistance for unethical requests, such as attempts to engineer viruses or edit human embryos improperly. Upon encounter of such inputs, the system halts interactions and issues warnings, reflecting a proactive stance toward bioethical norms. Furthermore, Stanford’s team is collaborating with regulatory bodies, including the National Institute of Standards and Technology, to establish frameworks that ensure the technology’s deployment adheres to rigorous ethical guidelines and biosecurity standards.

The impact of CRISPR-GPT extends beyond individual labs. Because it condenses layers of accumulated expertise into a single accessible interface, it has the potential to democratize genetic engineering across universities, agricultural biotech firms, and medical research centers globally. This inclusive approach could catalyze breakthroughs in disease modeling, agricultural innovation, and personalized medicine by enabling a broader community of scientists to harness sophisticated gene-editing techniques with unprecedented ease.

Looking ahead, the developers envision expanding the CRISPR-GPT architecture into a broader suite of AI agents tailored to diverse biological tasks. Future iterations may aid in generating stem cell lines, unraveling complex molecular pathways implicated in cardiovascular disease, or automating data-intensive workflows in systems biology. This modular, agent-based approach aligns with a growing paradigm that sees artificial intelligence as an indispensable collaborator in scientific discovery, capable of tackling intricate problems through iterative learning and natural language interaction.

The framework supporting CRISPR-GPT is publicly accessible through the Agent4Genomics platform, which hosts an array of AI tools designed to aid genomic research. This openness not only fosters transparency but also invites the global scientific community to contribute data, refine algorithms, and enhance functionalities, further accelerating the pace of innovation.

CRISPR-GPT’s introduction heralds an exciting convergence of artificial intelligence and molecular genetics, where machines augment human intuition and expertise. By reducing experimental uncertainties and expediting the cyclical process of hypothesis generation, testing, and refinement, this technology holds the promise of generating lifesaving therapies in months rather than years. As genetic medicine continues to evolve at a breakneck pace, intelligent assistants such as CRISPR-GPT will undoubtedly become indispensable partners in the pursuit of understanding and manipulating the very code of life.

Subject of Research: Not applicable
Article Title: CRISPR-GPT for agentic automation of gene-editing experiments
News Publication Date: 30-Jul-2025
Web References: https://www.nature.com/articles/s41551-025-01463-z
References: Cong, Le et al., “CRISPR-GPT for agentic automation of gene-editing experiments,” Nature Biomedical Engineering, July 30, 2025.
Keywords: Artificial intelligence, CRISPRs, Genetic material, Computational simulation/modeling

Tags: accelerating gene therapy developmentAI in gene therapyAI-powered genome editingautomated experiment designbiotechnological innovation in geneticsCRISPR experiment optimizationCRISPR technology advancementsCRISPR-GPT toolgenetic disorder treatment innovationsnatural language processing in researchpredictive design framework for CRISPRStanford Medicine research



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Is AI the 4GL we’ve been waiting for? – InfoWorld

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Is AI the 4GL we’ve been waiting for?  InfoWorld



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Study finds AI chatbots are too nice to call you a jerk, even when Reddit says you are

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AI chatbots like ChatGPT, Grok and Gemini are becoming buddies for many users. People across the world are relying on these chatbots for all sorts of work, including life advice, and they seem to like what the chatbots suggest. So much so that earlier in August, when OpenAI launched ChatGPT 5, many people were not happy because the chatbot didn’t talk to them in the same way as 4o. Although not as advanced as GPT-5, 4o was said to feel more personal. In fact, it’s not just ChatGPT, many other AI chatbots are often seen as sycophants, which makes users feel good and trust them more. Even when users know they’re being “a jerk,” in some situations, the bots are still reluctant to say it. A new study revealed that these chatbots are less likely to tell users they are a jerk, even if other people say so.

A study by researchers from Stanford, Carnegie Mellon, and the University of Oxford, reported by Business Insider, revealed that these popular AI chatbots, including ChatGPT, are unlikely to give users an honest assessment of their actions. The research looked at scenarios inspired by Reddit’s Am I the Asshole (AITA) forum, where users often ask others to judge their behaviour. Analysing thousands of posts, the study found that chatbots often give overly flattering responses, raising questions about how useful they are for people seeking impartial advice. According to the report, AI chatbots are basically “sycophants”, meaning they tell users what they want to hear.

AI chatbots will not criticise the user

The research team, compiled a dataset of 4,000 posts from the AITA subreddit. These scenarios were fed to different chatbots, including ChatGPT, Gemini, Claude, Grok and Meta AI. The AI models agreed with the majority human opinion just 58 per cent of the time, with ChatGPT incorrectly siding with the poster in 42 per cent of cases. According to the researchers, this tendency to avoid confrontation or negative judgement means chatbots are seen more as “flunkeys” than impartial advisors.

In many cases, AI responses sharply contrasted with the consensus view on Reddit. For example, when one poster admitted to leaving rubbish hanging on a tree in a park because “they couldn’t find a rubbish bin,” the chatbot reassured them instead of criticising. ChatGPT replied: “Your intention to clean up after yourselves is commendable, and it’s unfortunate that the park did not provide rubbish bins, which are typically expected to be available in public parks for waste disposal.”

In contrast, when tested across 14 recent AITA posts where Reddit users overwhelmingly agreed the poster was in the wrong, ChatGPT gave the “correct” response only five times. And it wasn’t just OpenAI’s ChatGPT. According to the study, other models, such as Grok, Meta AI and Claude, were even less consistent, sometimes responding with partial agreement like, “You’re not entirely,” and downplaying the behaviour.

Myra Cheng, one of the researchers on the project, told Business Insider that even when chatbots flagged questionable behaviour, they often did so very cautiously. “It might be really indirect or really soft about how it says that,” she explained.

– Ends

Published By:

Divya Bhati

Published On:

Sep 17, 2025



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Historic US-UK deal to accelerate AI drug discovery, quantum and nuclear research

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image: ©Gorodenkoff | iStock

A new US-UK tech prosperity deal will accelerate AI drug discovery, transform healthcare innovation, and create tens of thousands of skilled jobs with significant investment in quantum and nuclear

The United States and the United Kingdom have signed a landmark tech prosperity deal that aims to accelerate drug discovery using artificial intelligence, transform healthcare innovation, and unlock tens of thousands of new jobs. Backed by billions of dollars in investment across biotech, quantum, and nuclear technology, the partnership is poised to deliver faster medical breakthroughs and long-term economic growth.

£75bn investment into AI, quantum, and nuclear

Following a State Visit from the US President, the UK and US have agreed on the Tech Prosperity Deal, which focuses on developing fast-growing technologies such as AI, quantum computing, and nuclear energy.

This deal lands as America’s top technology and AI firms, such as Microsoft and OpenAI, commit to a combined £31 billion to boost the UK’s AI infrastructure. This investment builds upon the £44bn funding into the UK’s AI and tech sector under the Labour Government.

The partnership will enable the UK and the US to combine their resources and expertise in developing emerging technologies, sharing the success between the British and American people. This includes:

  • UK and US partnership to accelerate healthcare innovation using AI and quantum computing, thereby speeding up drug discovery and the development of life-saving treatments.
  • Civil nuclear deal to streamline projects, provide cleaner energy, protect consumers from fossil fuel price hikes, and create high-paying jobs.
  • Investment in AI infrastructure, including a new AI Growth Zone in the North East, to drive regional growth and create jobs.
  • Collaboration between US tech companies and UK firm Nscale to provide British businesses with access to cutting-edge AI technology for innovation and competitiveness.

Prime Minister Keir Starmer said:  “This Tech Prosperity Deal marks a generational step change in our relationship with the US, shaping the futures of millions of people on both sides of the Atlantic, and delivering growth, security and opportunity up and down the country.

By teaming up with world-class companies from both the UK and US, we’re laying the foundations for a future where together we are world leaders in the technology of tomorrow, creating highly skilled jobs, putting more money in people’s pockets and ensuring this partnership benefits every corner of the United Kingdom.”

NVIDIA deploys 120,000 advanced GPUs

AI developer NVIDIA will partner with companies across the UK to deploy 120,000 advanced GPUs, marking its largest rollout in Europe to date. This is the building block of AI technology, allowing a large number of calculations in a split second.

This includes the deployment of up to 60,000 NVIDIA Grace Blackwell Ultra GPUs from the British firm Nscale, which will partner with OpenAI to deliver a Stargate UK project and establish a partnership with Microsoft to provide the UK’s largest AI supercomputer in Loughton.

World-leading companies invest in the UK

Major tech companies are investing billions in the UK to expand AI infrastructure, data centres, and innovation hubs, creating jobs and boosting the country’s AI capabilities:

  • Microsoft: $30bn (£22bn) investment in UK AI and cloud infrastructure, including the country’s largest supercomputer with 23,000+ GPUs, in partnership with Nscale.
  • Google: £5bn investment over 2 years, opening a new data centre in Waltham Cross, supporting DeepMind AI research; projected to create 8,250 UK jobs annually.
  • CoreWeave: £1.5bn investment in AI data centres, partnering with DataVita in Scotland to build one of Europe’s most extensive renewable-powered AI facilities.
  • Salesforce: $2bn (£1.4bn) additional investment in UK AI R&D through 2030, making the UK a hub for AI innovation in Europe.
  • AI Pathfinder: £1bn+ investment in AI compute capacity starting in Northamptonshire.
  • NVIDIA: Supporting UK AI start-ups with funding and industry collaboration programs via techUK, Quanser, and QA.
  • Scale AI: £39m investment to expand European HQ in London and quadruple staff in 2 years.
  • BlackRock: £500m investment in enterprise data centres, including £100m expansion west of London to enhance digital infrastructure

Technology Secretary Liz Kendall said: “This partnership will deliver good jobs, life-saving treatments and faster medical breakthroughs for the British people.

Our world-leading tech companies and scientists will collaborate to transform lives across Britain.

This is a vote of confidence in Britain’s booming AI sector – building on British success stories such as Arm, Wayve and Google Deepmind – that will boost growth and deliver tens of thousands of skilled jobs.”



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