Now you can leverage multiple LLMs, for free, to help you get the best genAI deliverable while you experiment and choose your preferred infrastructure.

HuggingChat gives you a chat-based interface AND the ability to select from a set of different LLMs. You can run at least a few queries for free (I didn't hit a limit yet).

I wanted to see how they compared, and at the same time understand how well LLMs might help to implement a content strategy for the upcoming redesign of our 55BirchStreet website. So I chose a hypothetical example of a blog post about genAI and sustainability as a concrete example…

Even in a self-proclaimed 'AI business', understanding how to leverage genAI is not always widely distributed across the organisation.

Here's a LinkedIn job ad for a Group Product Manager at DeepL, a company I use regularly, value highly and respect greatly.

They have a great mission, "to break down language barriers for businesses and individuals around the world", and position themselves as "the world’s most advanced Language AI".

Yet when it comes to recruiting for a relatively key role in their product team, there is no mention of genAI in the job description, neither under Responsibilities nor Experience…

"I never use Google search for anything any more." 18 year old at a gallery during Berlin Art Week yesterday.

Basically, search is broken.He may have been exaggerating slightly, but I honestly get his point.I wanted to book a Berlin-Southend flight to visit family. I know the direct flights were pulled a few years ago, and wondered if they had been reinstated by now.

A 'quick' Google. 61 results on the first page alone. The actual answer is in there, but it's so buried as to be almost invisible…

The meaning of 'team' in 2024 has radically changed.

Collaboration, motivation and delegation - they are all still highly critical skills - but the context in which they are applied has expanded beyond human colleagues, to include a selection genAI 'collaborators'.

Is this really happening at scale today? It's tempting to think it's a case of 'the future is here just not evenly distributed', but that would be underestimating the growing waves already crashing on the shore.

Let's take two examples…

Last week's unveil of the Figure 01 was jaw-dropping. But the implications of industrialising this technology are even more breath-taking.

The initial demo already made it feel like we're living in the future. A humanoid robot that is dexterous, intelligent, can see, hear, converse, follow instructions and reason.

But think about it. With the capabilities that Figure has already developed, they've built their own flywheel.One of the first tasks at scale that the 01 can be deployed to do is to build more 01s…

In the vibrant yet cutthroat advertising landscape of San Francisco, two agencies, Quantum Creative and Narrative Edge, embarked on markedly different paths with the advent of generative AI, setting a dramatic stage reminiscent of a David Fincher narrative—complete with tension, intrigue, and an enlightening twist….

Most people had never used a mobile phone in 1984. And most of them wouldn't have wanted to.

Mobiles of that era had huge battery packs that you had to lug around, and were prohibitively expensive for the majority of consumers - pretty much strictly 'business only'. Basically they were for car-bound, high-powered executives and sales people, for whom being in constant contact made the expense and inconvenience a price worth paying.

If you'd stopped people in the street and asked if they wanted, needed, or were planning to get one - you can imagine the likely response.Fast forward to 2024. Now generative AI is in the same place as those early mobiles…

There seems to be a lot of panic on social media about the impact of generative AI on the creative industry. This was triggered by Sam Altman being quoted as saying that generative AI will do "95% of what marketers use agencies, strategists, and creative professionals for today."

Immediately and understandably, many people’s first reaction was that this sounds like a race to the bottom, where the primary currency is 'fast and cheap' as agencies struggle to cut costs and survive.

But it doesn't have to be this way. There are some really interesting alternative strategic choices ahead…

I’ve been wanting to try this for a while, ever since I got my HeyGen account activated last year, and am very excited to finally have time to conduct and share my experiment.

I was originally planning to try it out with a custom avatar based on my own image, but I decided to see how far I could get using free tools only. In some ways, that proved to be an even more fascinating journey…

The signs are that AI-generated content of all types will explode in 2024. The chart below is just an indication, but Amazon last year already had to limit the amount of self-published books an author could release - to 3 per day.

Yes - you heard right, 3 books per day - which means some people were releasing a lot more than that until the limit hit.

Given that AI struggles to detect AI-generated content, we will need a different solution to ensure we're not drowning in fake news, reviews and machine-generated books, articles, music, youtube content and podcasts…

I wonder if there will be any more 'why did it take so long?' moments in 2024. And for once I'm not talking specifically about generative AI, rather the shift in perspective needed to see where huge value can be created by something relatively simple.

Wheels on suitcases. First patented in 1945, the modern version patented in 1972. It took 15 years from then until it really started to take off, maybe helped by the addition of a retractable telescopic handle. (And maybe delayed by lingering male attachments to the demonstration of strength and masculinity.)

The 'why did it take so long?' feeling hit me again recently when I used a vacuum cleaner with an LED light built in for the first time. The light makes the dust stand out like nothing before! You don't miss any, and you get much more 'task satisfaction' having seen those easily-overlooked dust bunnies whisked away.

It's not as if people weren't trying to innovate…

It feels like the last 24 hours are showcasing two very different sides of generative AI. On the one hand we have the excitement and transformational utility of the new ChatGPT app store, on the other we have some of the first public announcements of "offboarding" directly caused by generative AI replacing work previously performed by humans.

Let's take the app store first, it looks good and has sensible categories, from Writing, to Productivity, Programming, Education and Lifestyle. Currently you can only see the top 12 GPTs in each category, for anything outside of that you have to use the search bar.

When you search, eg for 'business' or 'career' you get to see 10 results - plus any GPTs that you have created yourself that match your search term.

The excellent 'AI Breakdown' podcast speculated last week that one of the biggest challenges with GPTs would be discoverability - and I think they are right. If you're not in the top 12 featured GPTs, or coming up in the first 10 search results - it's going to be hard to be found organically….

An article in the New Scientist caught my eye this morning. It announced that EEG technology and AI have been combined to create a non-invasive thought-to-text device. The initial 40% accuracy rate is already increasing to 60% in the latest studies – so this has great potential - despite the ground still to be covered.

I have been an avid follower of developments in Brain-To-Machine (BMI) interfaces since 2012, and I was deeply excited by the AlterEgo experiments at MIT in 2018, but since then progress seemed to have stalled.

However with the advent of generative AI, I was confident that progress would accelerate rapidly, as generative AI is an accelerant for almost everything.

Prompted by today’s article, I had a collaborative session with ChatGPT to revisit our BMI assumptions and predictions…

Often it’s the sex industry taking the lead in adopting new technology, but when it comes to generative AI, the political establishment seems to be one of the first movers.

Just last week there were several reported instances of generative AI being leveraged to influence voters. The first, in Bangladesh, involved the use of deepfake videos to discredit opposition parties. The second in the US, reported on “Ashley”, an AI campaign assistant phoning potential voters and striking up a dialogue with them.

In the case of Ashley, a synthetic voice was consciously chosen so that it could not be mistaken for an actual human – but in other cases the technology is being applied to deliberately mislead voters.

The biggest issue isn’t how discernible the use of generative AI is, rather it’s the fact that if it is used at all, we can quickly end up in a world where nothing you see or hear can be fully trusted…

When I read about the 'lazy holiday' traits that ChatGPT has been exhibiting recently, I wasn't sure if is was real. But I tested, validated and found a simple solution...

I wasn't initially sure how accurate the reports were, because I have often experienced ChatGPT not fully complying with my requests, and this was in the Summer so not connected to any alleged 'holiday wind down'.

I always found that with some simple 'prodding', ChatGPT would step up and follow through on tasks fully.

Often ChatGPT would just give me a description or mini-guide for what needed to be done, and I needed to say something along the lines of 'I am really low on resources and time, so I need you to identify how an LLM could do this, with minimal human effort'.

With this additional instruction, ChatGPT would typically follow through with a revised list, and be ready to begin implementing it.

Now it seems, asking users to complete tasks themselves is one of the reported 'holiday symptoms' ChatGPT is exhibiting. I was really curious to find out if this was just what I had experienced and mitigated many times before - or a new season-related behaviour.

So I made a simple experiment…

As often happens, while reading an article in the FT app this morning, I speculated about some interesting possibilities that I wanted to integrate into my work.

Essentially, it all started from me imagining how cool it would be to have a ‘connect with ChatGPT’ button. This would let me deploy the learning in various ways, from LLM fine-tuning to a LinkedIn post.

Naturally, as a big believer in ‘learning by doing’ when it comes to genAI, I briefed Chat GPT to simulate this exercise for me.

Here is the LinkedIn post it created, as one of the outcomes from our interaction…

I came across this ad in a magazine in my hotel room yesterday, and it caught my imagination in terms of the future of AI celebrities.

Many articles about AI focus on how easily people might be replaced by AI, for example models.

In this case, as I looked at the images of Pierce and Paris, I imagined a different scenario. The images are certainly striking, since they are a great father/son pair - but I felt they were a little bit staged and stiff. Like they didn't really want to be there.

So I imagined, what if the shoot were created by generative AI? The Brosnans could have reduced their fee by 50%, and been paid for granting a licence to let AI generate their likeness in a campaign…

Did you ever dread sending a message or email involving a sensitive or complex topic? Did you ever send one and wish afterwards that you had worded it more effectively? Introducing ✨Message Mentor✨...

As you may have seen, I've been experimenting with the capabilities of GPTs, partly for their functionality, partly just to 'learn by doing'.

Yesterday I crafted Message Mentor, inspired by a message I sent to someone, and then realised afterwards that I could have worded it a lot more effectively.

In my case it was because I was feeling very frustrated when I sent it, but Message Mentor could help with any message that has a complex or emotional dimension. And it's useful for personal as well as business communications….

My approach to learning how to get the most out of generative AI, including understanding its limitations and how to work around them, is to experiment as much as possible - on low-risk use cases.

In fact, it's often a highly valuable learning experience to work on a topic only indirectly related to your professional role. Typically there is a lot of discovery that comes out of this process that applies to the world of work as well.

Here are some of the GPTs I have made since OpenAI launched the ability to create them…

Last weekend, ChatGPT and I created “Julianne Hartley”, a charming AI-author stirring hearts with "Whispers in the Mist”, first chapter published on Wattpad. (Full story in these three posts https://www.mikecbetts.com/julianne-hartley .)

I’m not planning to really manage an AI-author, but it was a really interesting ‘thought-experiment’ - how easy it is to create AI-generated fiction? How long would it take? How good would it be?

Well, it was easier than I imagined, and the results far better…