Category: AI
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Google’s AI-based research tool
Google has just revealed a new AI tool called Deep Research that lets you call upon its Gemini bot to scour the web for you and write a detailed report based on its findings.
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Please comment on the IFOMPT Generative Conversations discussion document
This post is an invitation to the wider physiotherapy community, asking colleagues to comment on a discussion document aimed at stimulating conversation about generative AI in the profession.
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Claude now has custom writing styles
You can now specify writing styles in Claude, which brings us one step closer to a world where the default behaviour is to use AI more often.
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Swarm is a framework for developing multi-agent systems
Swarm is an experimental framework from OpenAI, for building, orchestrating, and deploying multi-agent systems.
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How you use generative AI may say something about who you are
in AIHow you engage with generative AI may say something about how you work, what you value, and possibly even who you are.
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AI is not neutral. Neither is education.
While critics debate AI and education neutrality, they’re missing the point: nothing humans create is value-neutral, including education.
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The buttonification of writing
When you introduce a feature that makes it simple to use AI to generate writing, everyone is going to use the feature.
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Another surprising bit of initiative from Claude
in AII thought Claude was going to do what I meant it to do. But it ended up doing what I asked it to do instead.
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Generative AI in health professions education – Workshop for Tartu Health Care College
An overview of the workshop I facilitated for an audience of health professions educators, at the Tartu Health Care College in Estonia.
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Distributed agency in health systems – Norwegian Physiotherapy Association
In this short lecture for the Norwegian Physiotherapy Association, I ask “What if the healthcare system could think and act?” They key takeaway is that the health professions will need to evolve to take into account the notion of distributed agency, where accountability and responsibility for patient outcomes are shared by human-machine coalitions.
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The significance of OpenAI’s $6.6B investment round
OpenAI’s unprecedented $6.6 billion investment raise suggests they demonstrated something remarkable to investors, though not necessarily just raw intelligence gains. Whether it’s improved safety, efficiency, or multimodal capabilities, this massive vote of confidence hints at breakthroughs we haven’t yet seen publicly—developments that could reshape AI’s integration into society.
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Being inaccurate isn’t the same as being useless
New research on AI model factual accuracy shows that while language models struggle with certain difficult questions, this doesn’t diminish their value as thinking partners. Like human conversations, where perfect accuracy isn’t required for productive discussion, AI’s occasional inaccuracies don’t prevent it from being a useful collaborative tool.
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AI agents and physiotherapy – Scientifica conference keynote presentation
Reflecting on the near-term future of healthcare, assuming we will see the integration of AI agents and physiotherapy relatively soon.
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Diminishing returns of LLMs doesn’t stop progress
Recent discussions about LLM diminishing returns suggest OpenAI’s next frontier model may not be significantly smarter than GPT-4. However, this plateau in intelligence doesn’t diminish the technology’s potential, as improvements can focus on making models cheaper, faster, smaller, and better at specific tasks rather than increasing raw intelligence.
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AI-supported writing is a validity issue, not a morality issue
Moving beyond debates about ethics and style, this post reframes AI writing in academia as a validity issue. When students use AI for writing, the key question becomes whether we can still make valid assessments of their skills and understanding. This practical framework helps educators determine where AI support helps or hinders educational goals.
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AI-supported writing and confusing style with purpose
Moving beyond debates about AI writing’s “human element,” this post explores how writing purpose should guide AI usage. From technical documentation to personal reflections, understanding the intended purpose of writing helps determine when AI support is appropriate. The post introduces a practical suggestion for evaluating AI writing through purpose rather than style.
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AI-supported writing can be whatever you want it to be
I wanted to challenge the idea that AI-generated writing is inherently sterile, so argued that the quality of AI writing largely depends on how we interact with it. Through better prompts, iterative feedback, and personal editing, writers can create AI-supported content that maintains human qualities while leveraging generative AI’s capabilities.
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Testing your ability to detect deepfake images
Test your ability to detect AI generated images, with Northwestern’s deepfake image detector tool. I’m assuming this is some kind of research project.
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Court ruling: Language models don’t copy information; they synthesise it
in AIMasse, B. (2024, November 8). OpenAI’s data scraping wins big as Raw Story’s copyright lawsuit dismissed by NY court. VentureBeat. The judge noted that “the likelihood that ChatGPT would output plagiarized content from one of Plaintiffs’ articles seems remote.” This reflects a key difficulty in these types of cases: generative AI is designed to synthesize…