Wednesday, June 12, 2024

Apple solves privacy and security concerns around AI?

Apple Intelligence launched a set of AI features that had OpenAI’s GPT4 at the heart. It was a typical Apple move – focus on personalisation, integration and user performance.

The one thing that stood out for me was the announcement on privacy and ‘Edge’ computing. Their solution is clever and may give them real advantages in the real market. AI smartphones will be huge. Google led the way with the Pixel – I have one – it is excellent and cheap. But the real battle is between Apple and Samsung. The Galaxy is packed with AI features, as is the iPhone, but he who wins the AI device battle (currently 170 million units in 2024 and about to soar), will inherit users and revenue.

Privacy and security are now a big deal in AI. Whenever you shoot off to use a cloud service there is always the possibility of cybersecurity risks, losing data, even having your personal data looted.

Apple sell devices, so their device solution makes sense. It gives them ‘edge’ through ‘Edge Computing’.  A massive investment in their M3 chip and other hardware may give them further edge in the market.

In order to deliver real value to users the device needs to know what software and services you use across your devices, your emails, texts, messages, documents, emails, photos, audio files, videos, images, contacts, calendars, search history and AI chatbot use. Context really matters as if you are my ‘persona;’ assistant you need to know who I am, your friends and family, what I am doing and my present needs.

So what is Apple’s solution? They want to keep privacy on both device and when the cloud is accessed. Let’s be clear, Google, Microsoft, Meta, OpenAI and others will also solve this problem but it is apple who have been first above the parapet. This is because , unlike some of the others, they don’t sell ads and don’t sell your data. It pitches Apple against Microsoft but they are in different markets - one consumer, the other corporate.

‘Private Cloud Compute’ promises to use your data but not store and allow anyone access to your data, even Apple itself. Apple have promised to be transparent and have invited cybersecurity experts to scrutinise their solution. Note that they are not launching Apple Intelligence until the fall and even then only in the US. This makes sense, as this needs some serious scrutiny and testing.

Devices matter. Edge compute matters. As the new currency of ‘trust’ becomes a factor in sales, privacy and security matter. As always, technology finds a way to solve these problems, which is why I generally ignore superficial talk about ethics in AI, especially the doomsters. At almost every conference I attend I head misconceptions around data and privacy. Hope this small note helps.

Tuesday, June 11, 2024

Ethan Mollick’s 'CO-INTELLIGENCE' - a review

Just finished Ethan Mollick’s CO-INTELLIGENCE book. I like Ethan, as he shares stuff. His X feed is excellent, so was eager to give this a go.

It wasn’t what I expected, but that’s fine, because it’s pretty good. Ethan’s a Stanford academic, so I thought it would be a research-rich book with lots of examples but it is actually aimed at the basic, general reader, who knows little or nothing about AI; big font, big line spacing and no index but it does have some good, useful research.

It opens with his Three Nights Without Sleep revelation, that this shit is amazing! Why? Because it is a ‘General Purpose Technology’ pregnant with possibilities. I liked this. He writes well and is enthusiastic about its potential.


That sense of wonder continues over PART I, with his musings on the Scary? Smart? Scary-smart? Nature of GenAI, seeing it as a sort of alien mind. Alignment he thinks is necessary but is not a doomster and avoids the sort of speculative sci-fi stuff that often appears whenever AI and ethics is mentioned. He ends this section with his Four Rules for Co-Intelligence:

Always invite AI to the table – like this

Be the human in the loop – OK but…

Treat AI like a person (but tell it what kind of person it is) – like this

Assume this is the worst AI you will ever use – yip!


This is the bulk of the book, with five chapters, where he sees AI as a:






I have lots of quibbles but that’s fine. These are good, short readable discussions that open doors on its applications and potential. Each was well worth the read. I won’t go into detail, as I’d be in danger of providing one of those summaries that stops people buying the book!

It rounds off with a Chapter on AI as our future with four Scenarios; As Good As It Gets, Slow Growth, Exponential Growth or The Machine God. Then a short Epilogue, completed using ChatGPT – AI is US.

My own view is that the premise ‘CO-INTELLIGENCE’ is too simplistic and that it will do lots of things that will surprise us beyond the idea of just augmentation, a tool to enhance human creativity, decision-making, and productivity.

The problem with any book on AI, is that it is out of date before it is even printed. There were many points when I was thinking Yes… but… This is normal. The AI mindset demands fluidity and a recognition of the point Ethan makes in PART I – Assume this is the worst you will ever use.

Good introductory text – well worth a buy – but not for those who are looking for detail and depth of expertise.


Monday, June 10, 2024

Sam has ditched Satya for Tim – he’s so louche that lad! Apple Intelligence is here! New Siri and more...

Apple event features REALLY annoying presenters, but they finally join the GenAI club with Apple Intelligence. After showing the now compulsory ‘help me with my maths‘ example, they cut to the quick… it’s ChatGPT4 folks! 

Personal Intelligence

TTheir core idea is 'personal intelligence' as it understands your personal context. iPhone prioritises notifications, new writing tools (review, write and proofread etc) across all apps, even third party. Its email improvements, summaries of emails and so on, are super-cool. It will also intelligently prioritise your emails. Great for something I’ve been banging on about in learning – performance support. Apple are basically providing powerful, personal support across your entire online experience.

Images and video

On images it allows you to create images, including images of yourself, your friends and relatives, Sketch, Illustration and Animation styles built into apps across the system. Genmoji is a personal emoji creator, even an emoji that looks like your mates... that will be super-annoying. Image playground generation gives you styles, themes, costumes. Photoediting is super smart, getting things to disappear. Image wands allows you to circle, suggest and manipulate stuff.

There's also sound to text – great for student note taking and taking notes at work.

Search in video – clever. Great for performance support. Stories can be selected to a person and theme then strung together with music. Oh and there’s an API.

You can ask for personal stuff - remember that email I sent to... that picture I took of X last week... as it is personalising tools using personal data, the ‘who, what and whens’ of your life. 

Data privacy

This personal data is on-device processing so personal data is local. It can therefore use your personal data but with super-privacy features. An on-device semantic index helps keep it all local. Private cloud compute uses only data necessary for the task. It reaches out while still keeping your data private.


She’s gone from stupid to smart. Basically she’s now a chatbot that knows what you mean when you use ‘this’ and ‘that’ in sentences. It also has on-screen awareness and memory of what you have done. Siri knows your personal context – hotel bookings, photos you’ve taken, emails you’ve sent… porn you’ve accessed… no not that! 


What’s interesting is its agentic capabilities. It goes off and find stuff relevant to your request, flight info, external websites, things you’ve done locally. This has legs.

This is Apple, so it is integrated, user friendly and personal


One thing they have done well is the M3 chip, giving device AI functionality - that lay behind much of what was delivered here and may be critical in terms of practical and secure delivery of AI. It literally gives them 'edge' in the market. They're reallly a consumer company, unlike Microsoft (apart from games), which makes edge computing and iPhone delivery more important. Lots of the features were consumer oriented.

This is AI for the rest of us – not just work but performance support for life. Well done. Every generation needs a revolution and through this revolution we become more of ourselves.

Saturday, June 08, 2024

7 success factors in real 'AI in learning' projects

With AI we are in the most interesting decade in the history of our species. I can think of no better field in which to think, write and work.

Ideas are easy, implementation hard

My first AI-like project was in the early 90s when I designed an intelligent tutoring system to teach interviewing skills. It had sentence construction as input and adaptivity in the sense of harvesting data as the learner used the system. Written in Pascal, it was clever but not yet smart, as the limitations of the hardware, in terms of processing power and memory, were extreme by today’s standards. Much of the effort went into making things work within these brutal constraints. Even then, we had controlled access to video clips (36 mins), thousands of stills and two audio tracks 112 mins) on Laserdiscs, which we used to good effect, simulating full interviews. You could feel the power of potential intelligence in software.

Jump to 2014 and those hardware limitations had gone. You could build an adaptive, personalised system, which we did at CogBooks. I invested personally in this system (twice) and brought investment in. We did oodles of research at Arizona State University and it was sold to University of Cambridge in 2021. It worked. For many years we had also been playing with AI within Learning Pool having bought an AI company. But my real project journey with modern AI started in 2014, when we build Wildfire, using 'entity analysis', open input and the semantic interpretation of open text answers. The whole thing was starting to taker shape.

Jump to November 2022 and things went a little crazy. I have barely been off the road speaking about GenAI in learning, written books on the subject, blogged like crazy, and recorded dozens of podcasts. Far more important, has been the real projects and product we have built for a number of clients and companies. This is the hard part, the really hard part. Ideas are easy, implementation is hard.

Optimal AI project

What makes a successful AI project? What are the factors that make them a success? The good news is that we have just completed a fascinating project in healthcare that had all the hallmarks of the optimal project. This was our experience.

1. Top-down support

The project started with top-down support, a goal and budget. Without top-down support, projects are always at risk of running out of support. That’s why I’m suspicious of Higher Education projects, grant-aided projects, hackathon stuff and so on. I prefer CEO, Senior Management or Entrepreneur driven initiatives, with real budgets. They tend to have push behind them, clear goals and, above all, they tend to be STRATEGIC. Far too many projects are mosquito project that fail because they end when the budget runs out and have no real impact or compelling use. Choose your use case(s) carefully and strategically. We have been through this with large Global companies - a rational approach to use cases and their prioritisation. Interestingly, AI can help.

2. Bottom-up understanding

This project also had a great client, grounded in a real workplace (a large teaching hospital), a clear budget and solid team. We made sure that everyone was on the same page, understanding what this technology was and could do. The two non-technical team members knew their process inside out but here’s where they really scored – they made the effort to understand the technology and did their homework. This meant we could get on with the work and not get bogged down in explaining basic concepts such as how an LLM works, context window and the need for clean data and data management.

Many AI projects flounder when the team has non-technical members that don’t know the technology, namely AI. It is not that they need competence in building AI, just that they need to understand what it is, the fact that it evolves quickly and that its capabilities grow rapidly.

3. Optimal team

The team also had a top-notch AI developer who has been though years of learning projects. This combination was useful, He had already built products in the learning field, understood the language of learning and its goals. The team was just three people. This really matters. Use Occam’s Razor to determine team size – the minimum number of team members to reach your stated goal. Too many AI projects include people with little or no knowledge of the basic technology. They often come with misconceptions about what they think it is and does, along with several myths.

4. Mindset matters

More than knowledge, is mindset. What cripples projects are people within the organisation who act as bottlenecks – sceptics, legal departments who do not understand data issues, old-school learning people who actually don’t like tech and anyone who is straight up sceptical of the power of AI to increase efficacy. Believe me there are plenty of those folk around. 

The mindset that leads to success is one that accepts and understands that the technology is probabilistic, data-driven, that functionality will increase during the project and things change very fast. I’d sum this up by saying you need team members who are both willing to learn fast and keep their minds open to rapid change. It also means accepting that most processes are too manual, that bottlenecks are hard to identify and that processes CAN be automated. 

5. Agency shift

You also have to let go and see that this technology has ‘agency’ and that you will have to hand agency over to AI. The technology itself will reveal the bottlenecks and insights. Don’t assume you know at the start of the project, they will be revealed if you use the technology well. This is no time for an obsession with fixed Gantt charts and designs that are fossilised then simply executed. It is like ‘agile on steroids’.

6. Manage expectations

AI is a strange, mercurial and fast moving technology. You have to dispel lots of myths about how it works, the data issues and its capabilities. You also have to communicate this to the people that matter.
You need to understand that what is hard is sometimes easy and what is easy, sometimes hard. The fact that things change quickly, for example, costs, is another problem. This happens to be a good problem as people often don't understand that token costs for fixed output are very low and even token costs for a service have plummeted in price. Expectations need to be managed by being clearly communicated.

7. Push beyond prototype to product

I can’t go into a huge amount of detail about the client but the topic was Surgical Support  - a life and death topic, with little room for error. It involved training and taking source material and turning it into usable support (not a course) for hospital staff. Processes were automated, SME (Subject Matter Expert) time reduced, delivery time to launch massively reduced so the team had more time to focus on quality, as opposed to just process and easier to maintain, as just updating the documents means the system is always current. The savings were enormous and increases in quality clear.

This success meant we could call upon the top-down support to push the project beyond prototypes into product with a broader set of goals and more focus on data management. It has given the organisation, management and team the confidence to forge ahead. With massive amounts of time saved and increased efficacy, we saw that success begets success.


If you don't have both TOP-DOWN and BOTTOM-UP support along with a tight team with the right mindset, you will struggle, even fail. This is a radically new and different species of technology, with immense power. It needs careful handling. The small team remained fixed on the strategic goal but was flexible enough to choose the optimal technology. Without all of the above the project would have floundered in no-man's land, with scope creep, longer timescales and the usual drop in momentum, even disappointment. 

The project exceeded expectations. How often can you say that about a learning technology project? This was a young team, astounded at what they had done, and this week, when they presented it at a learning conference, their authentic joy when expressing how it went, was truly heartening. “It was crazy!” said one when she describing the first results, then further inroads into automating in minutes, jobs that had traditionally taken them days, weeks even months. Everyone in the room felt the thrill of having achieved something. In 2024 AI has suddenly got very real.


So many commentators and speakers on AI have never actually delivered a project or product. We need far more focus on practitioners who share what they think works and does not work.

Saturday, June 01, 2024

Postcreation: a new world. AI is not the machine, it is now ‘us’ speaking to ‘ourselves’, in fruitful dialogue.


There is an interesting idea from the French writer Bourriaud, that we’ve entered a new era, where art and cultural activity now interprets, reproduces, re-exhibits or utilises works made by others or from already available cultural products. He calls it ‘Postproduction’ I thank Rod J. Naquin for introducing me to this thinker and idea. 

Postproduction. Culture as Screenplay: How Art Reprograms the World (2002) was Bourriaud’s essay which examines the trend, emerging since the early 1990s, where a growing number of artists create art based on pre-existing works. He suggests that this "art of postproduction" is a response to the overwhelming abundance of cultural material in the global information age.

The proliferation of artworks and the art world's inclusion of previously ignored or disdained forms characterise this chaotic cultural landscape. Through postproduction, artists navigate and make sense of this cultural excess by reworking existing materials into new creations.


I’d like to universalise this idea of Postproduction to all forms of human endeavour that can now draw upon a vast common pool of culture; all text, images, audio and video, all of human knowledge and achievements – basically the fruits of all past human production to produce, in a way that can be described as ‘Postcreation’.

This is inspired by the arrival of multimodal LLMs, where vast pools of media representing the sum total of all history, all cultural output from our species, has been captured and used to train huge multimodal models that allow our species to create a new future. With new forms of AI, we are borrowing to create the new. It is a new beginning, a fresh start using technology that we have never seen before in the history of our species, something that seems strange but oddly familiar, thrilling but terrifying – AI.


AI, along with us, does not simply copy, sample or parrot things from the past – together we create new outputs. Neither do they remix, reassemble or reappropriate the past – together we recreate the future. This moves us beyond simple curation, collages and mashups into genuinely new forms of production and expression. We should also avoid seeing it as the reproduction of hybrids, reinterpretations or simple syntheses.

Like a ‘palimpsest’, a page from a scroll or book that has been scraped clean for reuse, we can recover the original text if we scan it carefully enough, but it is the ground for a genuinely new work. It should not be too readily reduced to one word, rather pre-fixed with ‘re-’; to reimagine, reenvision, reconceptualise, recontextualise, revise, rework, revamp, reinterpret, reframe, remodel, redefine and reinvent new cultural capital. We should not pin it down like a broken butterfly with a simple pin, one word, but let the idea flutter and fly free from the prison of language.


We have also moved beyond seeing prompt engineering as some sort of way of translating what we humans do into AI speak. It is now, quite simply, about explaining. We really do engage and speak wto and with these systems. The move towards multimodality with generated and semantically understood audio, is a huge leap forward, especially in learning. That’s how we humans interact.

Romantic illusion

We have been doing this on a small scale for a long time under the illusion, reinforced by late 18th and 19th century Romanticism, that creation is a uniquely human endeavour, when all along it has been a drawing upon the past, therefore deeply rooted in what the brain has experienced and takes from its memories to create anything new. We are now, together, taking things from the entire memory of our cultural past to create the new in acts of Postcreation.

Communal future

This new world or new dawn is more communal, drawing from the well of a vast shared, public collective. We can have a common purpose of mutual effort that leads to a more co-operative, collaborative and unified effort. There were some historical dawns that hinted at this future, the Library at Alexandria, open to all containing the known world's knowledge, Wikipedia a huge, free communal knowledge base, but this is something much more profoundly communal.

The many peoples, cultures and languages of the world can be in this communal effort, not to fix some utopian idea of a common set of values or cultural output but creation beyond what just one group sees as good and evil. This was Nietzsche’s re-evaluative vision. Utopias are always fixed and narrow dystopias. This could be a more innovative and transformative era, a future of openness, a genuine recognition that the future is created by us, not determined wholly by the past. AI is not the machine, it is now ‘us’ speaking to ‘ourselves’, in fruitful dialogue.

Thursday, May 30, 2024

Any sufficiently advanced technology is indistinguishable from magic.

Conference in Trondheim opened with a blast! A young brass band, confident and accomplished wakened us all up, followed by a primary school choir, not stuffed into school uniforms treated like recruits into the army cade core, but natural, willing and confident – it made the heart soar. They gave it their all, as did we in the audience – with thunderous applause. Their faces at hearing adults appreciate them was one of pure innocent wonder., as it should be. This is, after all, what education should be about, growing young people into being confident, autonomous people and giving them the knowledge and skills to thrive.

The Director of Education was up next and talked about the difficulties of having a National Policy and implementing such a policy, as like good teaching, it can’t be too didactic and lecturing and must have a tension between what is directed and what is devolved out to regions and schools. It was a balanced and honest talk, so unlike the hectoring we get from our own politicians and Civil Servants. He did, however, have a title for his talk which irked me – ‘There is no magic in the machine’. 

I understood his talk, in Norwegian, because the magic in the machine (smartphone) was translating his talk in real time. I understood the text on his slides as I was using Google Lens. Both of these, for me, are real but magical. Indeed, my whole keynote was about how technology has now become quite magical. I even had a slide saying as much, showing Arthur Clarke and his quote “Any sufficiently advanced technology is indistinguishable from magic.”

My turn next and with 1200 Norwegian teachers in front of me, like the kids, I praised than, as having seen their output the kids, they must be doing something right – and I meant it. Norwegians are relaxed, open folk who relish the fact that they live in a wild and mountainous country, so I cracked a joke about we Scots getting the Norwegian Vikings, while the English got the Swedish and Danish Vikings – adding that we got the real Vikings – they gave me a round of applause! Then added that my mother never called my three sisters and I ‘children’ or ‘kids’, always ‘bairns’ – the Norse word for children. I feel at home here and we Scots may be as close to their culture as England.

Anyway, I started with some avatar stuff, my Digital-Don with all of my writing in a chatbot, then OpenAIs recent magical release of ChatGPT4o being a maths teacher heling solve a linear equation, which it did in voiced dialogue. This was followed by another example showing the same software’s ability to teach trigonometry, this time recognising things drawn by the learner. Finally, I showed Google’s Project Astra, where the context is understood from just using a smartphone to recognise what is in the room, including objects, even interpreting code it is shown on a student’s screen. 

My point was that real teaching, or at least teaching support, is here NOW.  For the first time in the history of our species, a teacher can teach that most difficult subjects to teach and learn, maths, using what real teachers use in classrooms – voice, dialogue, structured feedback based on learner’s output. The difference is that it can teach any subject anytime, at any level, anywhere in almost any language. It is a UNIVERSAL TEACHER, something I’ve written about in my latest book ‘AI for Learning’. Learners will use it, parents will use it, teachers should be using it. The rest of my talk was about the affordances of this new AI tech, its engagement, the interface which is now speech, real dialogue and multimodal. I also showed real examples of learner support, learner deliver case studies, even its role in wellbeing. This is the real deal. 

Honestly, this was a great audience, none of that uptight, uniformed, boot-camp conformity, none of that lazy scepticism. They don’t have school uniforms, less crowded curriculum, have an enlightened set of routes out of schools, with a good, well-funded, vocational system.

I travel to a lot of countries and get to meet a lot of great people working in education and workplace learning. Travel, I think, does broaden the mind, and in this one respect, shows how others educate and train their young people. Sure others have their problems, like us, but they often have a more sophisticated view of schooling; not cramming them into uniforms, making them follow lines around the school in silence, an overcrowded curriculum, Sisyphean levels of administration for teachers, obsession with examinations and a brutal demand for conformity. Out and about every single young person I met as servers in bars and restaurants, in the hotel were confident, fluid in English and seemed happy at work. We seem to be trapped in some shadowing of public-schools nightmare, where neither teachers, politicians, learners nor parents are happy – it’s all so fraught. Harry Potter be damned.

Sunday, May 26, 2024

AI as response to digital transformation

Gave a Keynote in Cyprus, after the Minster gave a rather sobering speech about how Cyprus went bankrupt in 2013. The treasury was as empty as a robbed tomb and its three core banks collapsed in a greedy borrowing spree. It took a decade to recover but Digital Transformation, he reminded us, along with climate change and nearby wars, was one of their new challenges. 

I responded by saying the Digital Challenge just got more difficult as it is now led by AI. The European tech industry and organisations are being eclipsed by the US and the political response has been a flag-waving bucket of regulation. On top of this the EU has allowed most of the US Tech giants to evade tax by holing themselves up in tax havens like Ireland, stealing other countries’ tax revenues. Ignore AI and you have no Digital Transformation strategy as you become less productive and competitive in almost every vertical.

My talk focussed on recent announcements, real examples, things you can do now, fact that ChatGPT4 will soon be free, productivity research, using AI for recruitment, as a tutor and the need for top down as well as bottom up activity. They had asked for a 'wake-up call' talk. That was my aim.

Strategic implementation

Sripada Vittala, from Dubai, followed with a great talk in the implementation of AI projects. We had a great chat the next day and seemed to agree on everything, as we have both been through real projects and real implementation issues. 

He gave a great case study on how AI had dramatically impacted productivity, recruitment and retention in huge construction company. Trading notes was useful as we’ve been through several AI transformation projects and some common themes emerged. We both had the same experience in dealing with large companies. The need for a precise and structured workshop, where the participants DO things, then a vision identifying and prioritising use cases, pushing through beyond prototypes. Turns out our processes were near identical.

Toxic leadership

The second half, after lunch, focussed on other topics. Leadership, the topic of one talk, I think, is exaggerated and often badly implemented in workplace training. Neither am I convinced that slotting ‘Leaders’ into the toxic categories of Psychopaths, Sociopaths and Narcissists is right. Most bad management is much more mundane, to do with over-zealous drive to get things done, a sense of self-importance and, commonly, a lack of competence. We have seen this with Paula Vennels and the Post Office crew, including HR, along with their supplier Fujitsu, their PR folk and their Lawyers. We saw this at The Royal Bank of Scotland, the case discussed. They were a client of mine and the managers got away with truly toxic and incompetent behaviour but none were punished and the organisation was bailed out. That’s why Cyprus’s banks collapsed five years later – there was no effective regulation and punishment – still true today.


As for wellbeing, another talk, the evidence suggests that most workplace initiatives have little or no actual impact. I do feel that this constant focus on mental health is now a problem in itself. That is not to say it is not a problem, just that over-reflection on feelings, anxiety and mental health may not be the solution – it may make things worse. Denying that there are risks to therapy and interventions is a mistake, especially in your people with social anxiety. Thinking and talking about your problems all the time may not be good for you. CBT therapy confirms this, you need to break the spiral of negativity, not rise on its thermals. Being sad is not depression. A little anxiety isn’t always a bad thing. Being nervous is natural. You will get hurt emotionally. Getting hurt is not always trauma. Let’s focus on those with real chronic problems, not imaginary, self-perpetuated feelings that are often normal.


I'm not too sure why HR has got so obsessed by negativity and deficit thinking. I find that all a bit depressing! Nevertheless, this was a well-organised conference, short and sharp. The organisers were really efficient and hospitable. Sure there was a mix of speakers and topics, and we don’t have to agree with everyone, that’s good. The point is to make one think.


Thursday, May 23, 2024

Context matters? Yes and AI has made its move...

Just back from Japan and  our‘point and read’ Google Lens on the smartphone was a saviour. Japanese inscriptions in Museums, gardens, menus in restaurants, products in shops… using Lens was easy and reliable. No sooner are we were back in the UK, a rack of announcements from OpenAI, Google and Microsoft that put ‘contextual computing’ on the map. One of the primary problems in learning and performance support is CONTEXT. By that I mean, the teachers (human or AI) need to know WHO, WHAT, WHERE, WHEN to deliver great support. Context always matters.

Smartphone as remote control for life 

Where AI has been lacking is in knowing about your immediate context and intent. This nut is now being cracked, as AI’s multimodal abilities have now hit the market. By this I mean its ability to ‘hear’ things, ‘see’ through your camera, identify things from video or know what’s on your screen. Both OpenAI and Google have started to crack multimodal delivery. Whether it is text, images, speech or video – it understands. Microsoft have gone after your work tasks; what application are you using, what’s local on your PC. Copilot plus knows what you are up to so it can provide the right support. Agents are starting to understand you and your context so they can act as your assistant.

Your smartphone has become a robot that knows you. You can point at anything and ask questions. It’s a hearing, seeing, understanding thing, almost sentient thing. In a sense your smartphone is fast becoming a remote control for your life.

Context aids cognition

Context is a particular boon in learning, to help deliver learning, formative assessment and assessments in situ, even in imagined 3D spaces. We can transcend the tyranny of text to do so much more in the real world doing real things, with real people in real places.

In terms of performance support, you will be able to point your camera at anything and ask a question – what is this, give me more detail how I use this, teach me to use it…. You may need new knowledge, more knowledge, learn unfamiliar tasks, apply things, learn changes to familiar tasks… all of these famous ‘moments of need’ can be satisfied by contextual analysis.

If you are working on a screen, it knows what software you are using, what is in your document, image or PPT, what you need to improve in that document, image, PPT or spreadsheet. It may either help you or do that task itself. In a hospital you may get help in that specific radiology room, with that specific medical apparatus. In a factory it may know the machines, how to use them, get real health and safety in that specific area, show you what to do when things go wrong. You get the idea. Context aids cognition.


Widening the perspective, the introduction of ‘agents’ signals something else. These are entities that act on your behalf and may know what your overall goal, sub-goals and tasks are. It is here that agents come in. This is clearly a direction of travel with smart GPTs and recent announcements show agentic workflow, a fancy name for giving AI agents control to support you in specific tasks or goals. 

Moderna and other are using up to 400 agents within their organisations to help on specific tasks. With new agentic workflow, we will see significant productivity gains, as they literally automate what humans used to do. 

Context options

When discussing the context that computers can capture, we generally refer to the various dimensions that provide situational information to enhance the interaction between the user and the computer. It is worth identifying the sheer range of contextual support that is now possible:

1. Physical Context

Your smartphone has long used GPS, as well as local movements using accelerometer and gyroscope data to determine motion and orientation. It also knows what’s in the vicinity, that a traffic jam may hold you up. It also knows the time and date, holidays, calendar events, timezones, even the weather.

2. Personal Context

It knows your identity, not just information such as your name, age, gender, and possibly user profiles with data about your socio-economic status. A step further is what you are currently doing, often inferred from app usage, keyboard activity or wearable devices. Then there’s your ‘preferences’, such as likes, dislikes and preferences based on past actions, purchases and explicit settings. At the physiological level, your heart rate, stress level and other biometrics captured via wearable devices such as bands, watches and rings are knowable. Eye, head, face and gesture tracking can all be used to read you movements but also intentions. Voice may also be read for signs of emotion, stress, interest and intent. This can provide health and activity insights. You are a literally a mass of fixed and variable data as you move through the world.

3. Social Context

Don’t think it stops there, your social context inferred from social media identifies your friends, connections and interactions on social media platforms. Information about other users in the physical vicinity, which can be detected through Bluetooth, Wi-Fi, or other proximity technologies is also usable. Then there’s your long and detailed communication history on email, chat, call history, search and other forms of communication.

4. Cultural Context:

Not difficult to know the language settings of the device and the content you typically engage with to determines your socio-economic position and cultural interests. Bourdieu identified the forms this cultural capital takes in terms of your memberships, credentials, associations, the language you use, accent, sports you like and credentials you have and value.

5. Task Context

More specific task or application data can be gleaned from the screen, supplication or activity you are engaged in at that moment. Inferences can also be made from recently completed tasks or frequently performed actions, even transcripts from meetings. What are you watching, did you pause, cut out, review – all of these micro-behaviours are useful. Menus can be adapted to suit your preferences.

6. Device Context

What device are you on? A smartphone, tablet, laptop, desktop, wearable device, along with current battery status, can influence how the device manages resources. We may even know what bandwidth you have available on wi-fi, telecoms and so on, even available space on your device, CPU use and available memory.

7. Application Context:

What applications are currently in use and what is their state? Analysis of frequency and duration of tool and app usage can help predict future behaviour, even permissions tell a story.

All of the above can be used to provide personalised notifications and reminders or sell you stuff with targeted advertising. By integrating these various dimensions of context, computers can offer more intuitive, responsive, and personalized user experiences.


Context is the new frontier for computing and with edge computing, local AI and agents, we can see how much work can be made more efficient. This scales people, which is what most organisations, wallowing in flat of slums of productivity need. We also have to be honest and admi that they may automate what humans thought they needed to do.

Tuesday, May 21, 2024

AI Business Boats don’t rise with these models, they remain tethered to the old dock and sink.

Sinking businesses?

AI businesses are getting steamrollered by OpenAI & others. Business cases have to be moated against attack by the new releases, as the new model will do what you do but quicker, better & cheaper. Boats don’t rise with these models, they remain tethered to the old dock and sink.

The trend is towards huge compute, large models with massive investment, effort and expertise to build and role out. Your service, built on top of the model is simply done better by using the model directly. This makes AI different from all other technology we have ever invented.

The internet created millions of businesses as it was an empty platform. AI is abundantly rich, deep & wide, trained on content that takes hundreds of 1000s of years to read. We will never catch up. The internet was a sea on which we could all sail. A LLM is an ocean that can gobble us up.

The problem is that many businesses are also tethered to this old internet model, with proprietary content and platforms,. which are slow, shallow, difficult to use and functionally limited. Intelligence has been unleashed on a new platform tat is easy to use, multimodal and fast.

ChatGPT4o will make GPT4 available for free. This is astonishing, so much power, for free, perhaps the one feature that will change things the most in their announcement.

You have to make some big bet strategic decisions as a startup.

Bet 1: LLM scalability and progress will run our of steam, allowing faster and betters products to build upon their limited success. If you get this wrong you sink.

Bet 2: Open source products will be available that have the same functionality as closed proprietary models. Here you have a chance to float on the open source movement. 

Bet 3: Build around the success of the behemoths , with consultancy, projects for large companies and so on but that doesn't give you the big revenues you imagine.

In the end you are betting against entities that have huge amounts of capital, the ears of investors and the ability to deliver. Talent is also in short supply.

So what is the new business model(s)?

Hackathons are interesting as they tend to flush out all the low hanging fruit and use the existing models and services to get things done. Most of the this low hanging fruit is rotten by the time it hits the ground. What it does do is establish business demand and use cases.

Multimodality in all its forms, huge context windows and ability to read the screen through Co-pilot have laid waste to developed applications.

So one must identify where you lie on the supply chain.

If you are building some extra functionality on top of a model, but using that model for delivery, the danger is obvious, that an improvement in the model can eat you alive.

If you have a unique asset that can be used for access, such as a large publisher, you stand a chance if you can prevent leakage.

If you have part of a service that AI does not deliver but enhances, you have a chance.

Devices - forget it.

Road to monopolies

This is a worry, as this is the road to monopolies, possibly even a single monopoly, as we may get a runaway effect where one model excels and outperforms all others. The singularity may be in business. This is worrying and governments are ill-prepared to deal with this.

They compete with each other to offer low tax regimes and companies take advantage of this. Even in supra-national entities, like the EU, have massive tax theft by allowing the large US tech companies to set up shop in the lowest tax regimes, largely Ireland.

Some may succeed but, by and large (literally), the trend is towards huge compute, large models, fine-tuned that take massive investment, effort and expertise to build and role out. Your service, built on top of the model is simply done better by users using the model directly. This is what makes this technology different from any other technology we have ever invented. 

Altman and many others have observed the disaster that is the European Tech industry. It gets crushed by negativity, bought out by the US and strangled by regulation. The problem is not AI but politics and economics. We need to get this sorted and fast.

Friday, May 17, 2024

Does this 'Her' moment mark the rise of AI coaching?

I now have ChatGPT4o on both my phone and desktop. It’s not until you start using it that you understand how good this is.

We started, my son, wife and I just chatting generally and it was immediately mind blowing, natural, friendly, inquisitive. We kept looking at each other as if to say ‘Holy shit!’. We even asked to translate this Scottish dialect sentence “We’re goin doon the street for the messages.” She translated it accurately as going shopping!

I then started to speak to it in French abut our impending holiday and it did a great job, even telling me the distance in Kilometres on the route. That gave us an idea – using it to teach a foreign language. It asked her to play the role of a friendly language tutor and she did, with gradually more complex phrases and questions, recognising when I got it right asking again if I got it wrong. This is real dialogue as if she were a real language teacher.

A friend, on social media, then asked me if it could teach Sorani or Tingriyan. I thought the latter may be something from Game of Thrones, that’s how little I know about these languages but… she started to teach me both when I asked. This is sort of mind blowing as the teaching of languages is an area of catastrophic failure in schools. This may well be the answer, as it is endlessly patient, personalised and available 24/7 on any phone.

Moving on I got her to play coach, a life coach, then leadership coach, then leadership coach based on Blanchard’s Situational leadership. All worked. This is interesting, as you can get it to coach from one theoretical basis. One wonders whether the whole coach, mentor, councillor, therapist industry will be decimated by this?

‘Her’ moment

To be totally honest, I’m not a great fan of the coaching, mentoring and counselling industry. That’s not to say it is of no use, only that I feel it is bloated and, as people love talking about themselves, is often built upon this and this alone. There are several ways this could shake out, as dialogue-based technology has suddenly got super-good:

1. It expands the human-to-human coaching industry (zero probability)

2. It eats into this market replacing much human coaching (high probability in short term)

3. It decimates this market (high probability in long term)

Note that I have no idea what the gap between short and long-term will be. But if we look at what has panned between ChatGPT3.5 and ChatGPT4o – things are moving faster than expected.

The launch of ChatGPT4o, the ‘Her’ moment in the industry has changed this game and made progress on this front, with very smart ‘dialogue’ turn-based, emotionally intelligent, multimodal chatbots. OpenAI were smart in using this meme to launch 4o, as it is spot on. With advances in realtime avatars, which are coming soon, we can expect 2. to move to 3.

Advantages of AI coaches

This may sound odd but there are several affordances around chatbots that may make them preferable for some:

1. Multimodal dialogue

2. Emotional recognition

3. Dialogue

4. Patience

5. Anonymity

Multimodal. Young people text ALL THE TIME. It’s easy and normal. They don’t necessarily want full blown speech dialogue (although of you want it you can have it). It is the quiet, low key nature of text that is calming and can be read at your own pace. Then again, this misses the social, body language and other cues in dialogue that may also help. The good news, as we saw above, is that it will all be possible. You will be able to choose your mode of dialogue, from text to full blown avatar.

Emotional recognition. This will be a feature in ChatGPT40, the recognition of emotion in your voice, opening up the possibility of more nuanced conversations.

Dialogue. This is the key to therapy. You want to be heard and listened to with calm, useful feedback. Dialogue is what our brains have evolved to do and these bots are good at it. With current chatbots you can also have an immediate transcripts of the conversation. This can be used by AI to recommend real things you can do after the session, even critique how it went.

Patience. This, they say, is a virtue and in this context a necessity. You want the quiet confidence of an endlessly patient and empathetic character, who is never impatient or snarky.

Anonymity. This is, I suspect, the secret sauce. Young people are unlikely to go to their parents, teachers, even friends through embarrassment, so they suffer in silence. The anonymity of a bot allows one to express feelings you would not to people you know.

I’m sure people will say that it needs a human to give counselling. I’m not so sure. For many this light touch may be enough. If not, you can move on to find a sympathetic soul. As a first door, it serves a purpose, of maybe even soothing those who are temporarily troubled. Sad rather than any real mental illness. We can rush to label negative emotions as deficits, even pathological, but sometimes making people realise they are not alone in having such thought is enough.

Realtime avatars

Realistic Avatars are already being used in marketing, training and other contexts. I have Synthesia and Heygen avatars. These are all pretty impressive technically and, more importantly in terms of impact. I’ve shown them to audiences around the world and they literally ‘wow’ audiences. I have used them in multiple languages from Norwegian to Zulu. 

This June I will be back in the Synthesia Studio to create a hyper-real version of myself. This is a real advance to the level of looking and sounding like me, with my strong Scottish accent.

Personal chatbots

As well as my avatars, I have a Chatbot (Digital-Don) that allows you to ask me questions, answering using almost everything I’ve ever written. Believe me this is impressive. It uses OpenAIs GPT service (RAG) and does a brilliant job. I find myself asking myself things about things my resent self has forgotten. It is like speaking to a better version of yourself, with a great memory! The opportunities for everyone to have such a chatbot is already here. Any expert, academic, writer can have one. Moderna has rolled out 400 expert chatbots to perform most of its corporate functions. We will see a lot, lot more of this.

Games and NPCs

We also have services producing realtime avatars that you can chat to in real time. They are already available in games. Nvidia’s ACE (Avatar Cloud Engine) for Games brings real-time conversational AI to in-game NPCs (Non Player Characters). This technology integrates text-to-speech, natural language understanding, and facial animation to create responsive and lifelike NPCs. They have produced a player that can interact with a shopkeeper NPC in real-time within a cyberpunk setting, showcases the potential for future game integrations. ZREALITY has developed spatially aware virtual assistants using ChatGPT and Ready Player Me avatars. These assistants can navigate 3D environments and interact with users in a natural and intuitive way, providing real-time support and enhancing the user experience in various applications. Roblox has announced a new generative AI-based character creator. Ubisoft has also demonstrated its NPCs or NEO NPCS, in partnership with Inworld AI. They use LLMs and are quite simple at the moment, as David Louapre says, more “roleplay than gameplay” but we will undoubtably see lots of this emerge as mods in tools such as Unity. 


Some years back I came across a small poem and candle on Beachy Head cliffs. It was placed there by the parents of a young girl who had thrown herself of the cliff due to her poor exam results. It shocked me then, it shocks me now, that someone so young could summon up the strength to do that. It hit me like a train.

Psychologist, a Chatbot on Character.AI, one among many, seems to do exceptionally well. It gets 3.5 million hits a day! The idea is simple, it delivers standard CBT therapy as dialogue, just like a real counsellor or therapist. It's chatty, helpful, endlessly patient and unlike human support is available 24/7.

Isn't it odd that something that is text only, simple dialogue is so wildly popular? It does not surprise me, as since ELIZA, developed way back between 1964 to 67, people have loved these bots. Even that version, which was quite primitive keyword reflection fooled people into thinking it was human. We know from Nass & Reeves, even the movies, how easy it is to get people to think that what they see and hear is human, especially what they see as meaningful dialogue.

Seven years ago, I tried Woebot (Woe is me… my 10 days being counselled by a chatbot (woebot)) a counselling chatbot. I rather liked it.

This was way before LLMs and ChatGPT and I wrote a ton in my book ‘AI for Learning’ about how powerful dialogue chatbots would become, including those for wellbeing. 

Then along came ChatGPT – suddenly it happened, we shifted from monologue to dialogue. It changed everything! These large language models capture vast amounts of language. When you speak to ChatGPT you are speaking to ourselves, the human hive mind. One of their great strengths is that they really do present human dialogue as the means of learning. They humanise learning but also coaching.

These wellbeing bots really have now taken off. ‘Psychologist’, probably the most popular from, is pretty good. The dialogue feels natural, like talking to a real person and the advice, largely a CBT approach is pretty sound. Fast and short chat, it gave me a pretty good summary of CBT:

“Cognitive Behavioural Therapy (CBT) is a type of psychological therapy which focuses on the relationship between thoughts, feelings and behaviour. The key principle of CBT is that thoughts affect feelings, and feelings affect behaviour.

The aim of CBT is to help people change their thoughts in order to improve their emotions & behaviours. It does this through identifying and targeting problematic patterns of thinking, as well as working on techniques to challenge and replace these thoughts with more rational and adaptive ones.”

It’s been around for just over a year and has clocked up some pretty impressive stats at 78 million messages, 18 million since November. You’re talking about millions of individuals talking with it every day.

Some of the people using the bot simply respond by saying they are lonely and just needed to chat to someone. Why not? I can see these being part of our counselling landscape in the future, they already are. The problem here are humans, who sometimes push people into places through pressure, even bullying. Let’s not think that being human can be Panglossian. We all live lives of quiet desperation to some degree and we all need a shoulder to lean on sometimes. Let that shoulder be a friendly chat at any time, from anyplace on anything.

In an absolutely fascinating paper by Maples, B., Cerit, M., Vishwanath, A. and Pea, R., 2023. titled Loneliness and Suicide Mitigation for Students using GPT3-Enabled Chatbots, 1006 student users turned out to be more lonely than typical students. One third of the population suffer from loneliness, 1 in 12 are so lonely it causes serious health problems and suicide is the 4th global cause of death 15–29. With the Replika bot, 3% reported it halting suicidal thoughts.

The research on therapy bots, with large audiences, is that young people especially value the anonymity of the technology - they do not go to parents, teachers of faculty - they suffer in silence.


Once realtime avatars comes in and they become hyper-real then the human dimensions of dialogue (body language and other contextual and social cues) can be achieved. Coaching, mentoring and counselling will not disappear but it would be foolish to imagine it will be untouched. It has already had huge audiences and will continue to grow, in part replacing these services. 

One of the problems coaching bots will face, will be the simple fact that they may not be adding much value. Simply asking OpenAI or another service may suffice. However, there are lots of niches where these tools still help. These vary from simulating difficult conversations through to identifying your leadership style by tracking what you do in meetings – and everything in-between.

With AI, we’d be wise to take Wayne Gretzky’s advice and "skate to where the puck is going to be, not to where it has been."

Wednesday, May 15, 2024

Google just dropped some great news on AI for learning....

OpenAI drummed up a great PR campaign with leaks around the movie ‘Her’ and Altman hints. What many missed was another launch by Google. That’s how fast this stuff moves.

More than this they published a paper we in the learning game should all read. Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. It has 75 authors!

What the paper does is address a BIG issue – getting learning insights into GenAI.

Excitement is brewing over the potential of GenAI to revolutionise learning by providing a personal tutor for every student and a teaching assistant for every teacher. The OpenAI launch was fantastic and showed real opportunities and promise. They out Appled Apple with their focus on user experience and functionality.

However, this vision is still not reality, mainly due to the complexity of translating learning insights into effective AI prompts and the lack of robust ways to measure AI's teaching effectiveness. SO Google teamed up with learners and educators to turn broad educational theories into practical evaluation benchmarks. This is a mix of quantitative and qualitative measures, both automated and human-led, and they have developed new training datasets to enhance the educational skills of their GenAI system, LearnLM-Tutor. 

They claim to be achieving  great results from LearnLM-Tutor over other models because of its superior teaching abilities. They would say that, wouldn’t they. But I’m impressed, as this work lays the groundwork for a comprehensive framework to assess educational AI, potentially accelerating GenAI's positive impact on learning.

What this report does is look at the use of GenAI to enhance education through AI-driven tutoring, particularly focusing on conversational models. Their approach utilises Supervised Fine-Tuning (SFT) with data informed by educational principles, improving the AI tutor, LearnLM-Tutor, beyond the Gemini 1.0 model. 

They are honest about the challenges, especially in defining and achieving true pedagogical mastery with AI. Collecting a diverse range of high-quality pedagogical data is costly and labour-intensive, and it is unclear how many examples are necessary to comprehensively cover pedagogical behaviours.

So they have  established a set of benchmarks to evaluate their progress, although these too have their limitations—especially the expensive nature of human evaluations. To address these issues, they have put together a  multidisciplinary team, including AI scientists, engineers, pedagogical experts, and cognitive scientists, to work on refining these evaluation methods. This collaborative effort aims to not only enhance the current AI models but also invites the broader AI and learning science communities to join in enhancing and utilising these pedagogical benchmarks. Their ultimate goal is to leverage AI effectively to benefit learners, pushing forward the boundaries of learning technology. More power tyo their elbow.

Google is Google. They don’t do product launches like OpenAI, they integrate things into their world. They have a global view of technology, which means integrated. Don’t write them off.


Monday, May 13, 2024

Is teaching becoming obsolete with GPT4o? Do we now have a UNIVERSAL TEACHER?

I have written and talked about the idea of a UNIVERSAL TEACHER for a long time, notably in my new book, where I go into detail about the learning theory behind 'dialogue' in learning and the key role of chatbots in teaching and learning. This is what AI promised to deliver. A free teacher who speaks, listens, remembers, tutors, using all media types, can read handwriting, provide personalised feedback, on any subject, anytime, anywhere, in any language.

What I never imagined was that it would come so fast. Yet OpenAI has delivered on what I thought was this utopian idea. In their demo they showed this in action. A frictionless, fast and sophisticated tutor. 

Open AI has become the Apple of AI. They understand, like Steve Jobs, that the user experience is all. This is especially true in teaching and training. Of all the applications, teaching and learning is the one that has most to gain from GPT4o. They may have out-Appled Apple, as Siri, Google assistant and Alexa are nowhere near as good as this. At this rate, teaching is rapidly becoming obsolete.

Realtime teacher dialogue

You can chat with it in realtime as it has realtime speech and, in the live demo, understands your voice, your emotions as expressed through your voice, even your facial expressions. You can have dialogue just as you would with a real teacher, you can interrupt it and it responds fast, as fast as a real teacher. It can generate a teacher’s voice in many styles – funny, friendly, serious, academic… whatever. The teacher’s voice is extraordinarily realistic.


Real maths problem taughtThere was lots of pre-launch chat, stimulated by Altman, about the movie 'Her'. We now see why. The system is very 'chatty'. Indeed the fact that you can define the character by asking it to be someone, is astounding. This is a shift in branding away from Google's serious sounding assistant towards a real, emotional definition of a chatbot, so that it can play any defined role. The possibilities from different type of teachers, tutors, trainers and instructors to role playing with patients, customers and employees, even therapists, are endless.They showed a maths problem, with the learner doing it on paper, the handwritten problem, then shown to his smartphone. 

He shows her a linear equation:  3x+1=4. 

The tutor suggests he get all numbers on one side, giving a hint.

He subtracts 1 from both sides to give 3x=3. 

How does this look? He asks.

She congratulates him.

He asks for a hint for the next step. 

What undoes multiplication? She asks. 

He suggests subtraction but she says, think of the opposite of multiplication. 

He says division? 

Go ahead and divide both sides by 3 she instructs.

He does this and the solution is x=1

Well done you’ve solved it, she replies.

He then asks for real world applications and she gives him several. The tutor is endlessly patient, friendly, gives relevant feedback and can read his written steps in moving towards a solution.

n another teaching problem, by Salman Khan, you ask it to be a tutor and it talks you through a maths problem around the sides and angles in a right-angled triangle. There’s great back and forth dialogue between the student and AI, with hyper-personalised feedback and reinforcement. It does everything at the pace of the learner, behaves just like a patient tutor and corrects any errors the learner makes. All by simple showing the problem and the learner’s efforts to his smartphone. Although one has to be careful with staged examples, as it isn't doing much 'hard reasoning' here. That may be there already, it will certainly come. There is also the issue of having to show it an image, the next step is surely to draw and write on the screen as an option.

I wrote about Khan almost a decade ago, saying he was an important figure, way beyond Robinson, Mitra and many others. OpenAI have been wise in teaming up with Khan on education.

Some great features in this teaching video. For examplewhen the tutor is talking, if you start speaking, it stops and waits for your response. Focus on the voice of the teacher - it's very neat. The intonation is also interesting, teacher-tone. and it can be adjusted to suit any individual or audience. Its endless patience removes the frustration that every teacher and parent feels when teaching, as it defuses the stress.

One thought I did have, which is almost existential - if it can teach and do all of this maths, why would we teach it. Roger Schank used to go on about this a lot - why teach skills that can be automated, especially algebra and geometry? In any case the focus is often on maths as that is an area of catastrophic failure for many kids and adults. Maybe AI will solve the problem by solving the maths itself, not teaching millions to do what can be done in a millisecond by voice and AI.

Multimodal teaching

As a teacher it can read text, recognise images and video, just like a real teacher. In another example, the voice app on your desktop helps the learner solve a code problem, understands the written code on the screen, also the voice of the learner. She explains what the ‘foo’ function is, step by step. More than this you can then ask it to see the data visualisation that the code produces. Ask it questions about the graph and itinterprets the graph for you. So it can teach you maths, code and data analysis.


It also does real time translation, so you can teach in one language, give feedback in another, great for people learning in a second language. The possibilities in language learning are also mind blowing.


The accessibility featured of GenAI often overlooked. I bang on abut this all the time and has just been boosted by GPT4o. Text2speech, speech2speech, now highly personalised dialogue. 'Bemyeyes' with GPT4o is amazing. The fact that it is free is also a huge boon for access by the poor and all who are excluded due to cost.


There was already an administrative function at enterprise level for GPTs, already used by some global companies, such as Moderna. This will be extended. It is at this organisational level that they will make money.


GPT4o is better than GPT4 and hammers other models. It is also faster and smarter across text, vision and audio, truly multimodal. What have they done and how? Behind the scenes the optimisation needed to deliver low-latency audio to audio in real time is massively impressive. This is not trivial as dialoghue overlaps, interrupts and is difficult to map This is a huge leap on ease of use in dialogue and intelligence with low latency, necessary for the smooth dialogue needed in tutoring. It reasons across text, voice and vision, making the teaching experience seem like a real human teacher. This could revolutionise teaching, accelerate learning, even accelerate home-schooling, maybe the end of the personal tutoring business. I feel that this is a game changer for parents as well as teachers. As a first step this is astonishing, as it is a globally scalable solution to a problem that has plagued education, where teacher shortages and costs are a problem. This is a great leveller.

The fact that the branding is GPT4o is tantalising, as if they have something else up their sleeves - GPT5? But what they have done is redefined AI as something that becomes more human using dialogue. This shift in our relationship with computers is fundamental.

Of course, this still needs testing across a range of examples but this is an astounding start. There is no stopping of progress here, the UNIVERSAL TEACHER will happen, and soon. The future is now.


Noted they were using iPhones and a deal was stuck yesterday with Apple - something very big is brewing there.

Friday, May 10, 2024

Japan - a lesson in life and technology

Remember when Japan was the exemplar of Capitalism? We were all urged to learn Japanese. It is now seen as a frail economy.  The yen's plunge to a fresh 35 year low against the dollar makes things cheap here and could result in a resurgence of inflation via higher costs for imports of food and energy.  Japan is a major emitter of greenhouse gases, plastic is used everywhere and it still has significant coal production. It now plays little role in Foreign affairs and you rarely hear the Japanese voice on global issues. Yet it is still an astoundingly vibrant and beautiful place. So, how has Japan managed to keep going in the face of mounting debt? They use a scheme of monetising government debt, where the Bank of Japan purchases government bonds to finance the government's spending needs. 

Once a tech giant in cars, robots and games consoles, it also seems to have lost its innovative mojo. China looms large over its shoulder and the ‘robot’ stuff I saw was dated. Tech means toys here, with vast emporiums for toys and kids’ tat, entire shops with toy vending machines. 

One wonders at the effects of a culture of extreme conformity. There is barely a surface that does not have a sign telling you want to do, where to go and what to buy, even multilingual announcements telling you not to speak into your phone on the Metro, people guiding you with batons. The upside is the polite, quiet, calm, safe, aesthetic, almost serene environment, even in an immensely crowded city like Tokyo. It is a frictionless city, easy to move around, no hassle.

The downside, I can only guess, but I’m told a suffocating sense of personal, peer and parental pressure. The Lolita Gothic girls, the 2 or 3 hour hotel rooms for sex (they’re everywhere), used by couples who don’t have privacy at home, the almost pathological use of smartphones - standing, sitting or walking, people are staring at their screens. Howard Rheingold wrote about this in the 90s, when Japanese kids adopted the cellphone faster than any other nation on earth, as they had little privacy and saw it as a social release. Its success came though consoles and games, also the mighty Sony.

One symptom of its problems, and what you don’t see, are the ‘hikikomori’ who never leave the house, not just the young and not just young men. They spend months and years in their home, often in one room, with no social contact, like post-modern hermits. The causes seem to be a tendency toward conformity and collectivism, some autism, overprotective parenting, a pressured educational system, housing supply and now a problematic economic system. 

The most widely reported cases of hikikomori are from middle- and upper-middle-class sons, who refuse to leave the home, often after experiencing a traumatic episode of social or academic failure. They often start by refusing to go to school. Co-dependency between mother and son, known as ‘amae’ is also a problem. People are looking inwards not outwards, avoiding social situations. 

Japan now has one of the oldest populations in the world, with a huge number of elderly citizens and low birth rate. This has led to a shortage of workers and increased costs for welfare, healthcare and pensions. A draconian nationalist immigration policy means no relief.  Jonathon Haidt has talked about similar problems in the US and we see signs of this in many countries. This sense of an educational system that was full of promise and expectation but results in disappointment is what Turchin calls the over-production of the elite. The giving up on having children, a retreat into one’s self, is a worrying sign for any society.

One caveat. Having read MacFarlane’s excellent ‘Japan Through the looking Glass’, I’m aware of seeing only the surface. This is a complex culture with complex problems. It is easy to see the flaws and not admire the, albeit subtle, depth of Japanese culture, especially from more bellicose cultures that worship individualism. The place and people are amazing.