You will not be able to keep up with the pace of AI innovation❗️

Earlier this week I had the opportunity to participate in the super inspiring "AI trends seminar" arranged by AI Sweden. I have been following AI development from the side for a couple of years, and in the last 3 months or so we have seen an explosion - incredibly stressful if trying to stay on top 😅.

In one week, I counted over 100 new AI-applications in my LinkedIn-feed, each of them promising to "10x my productivity" and I do not use any of them 😱 
 
Daniel Akenine from Microsoft was one of the speakers at the AI Sweden event, wow what a great talk 🤩 One thing that stayed with me was he saying something along the lines with  
 
- The AI development is too fast for most of us to keep up with, and that is fine. 
 
It felt exceptionally good hearing that. I am taking with me to being T-shaped, i.e., focus narrowly on the AI-development that is relevant to me and just browse what is happening outside my core. 
 
How do you stay on top of the developments in AI? Try to stay on top or relax until the dust settles? 
 
💡 AI Sweden is doing a wonderful job at enlightening us on AI, one relatively effortless way to stay informed is to join their "my ai" service - I think it will cover the needs for most of us.

FOMO to FOAI: Finding Your Way in the Flood Of AI Applications

How I found my way in the flood of AI Applications

Ah, the early days of the internet. Back in the late ’90s, when we tech-savvy types were just getting our first taste of this fresh thing called the World Wide Web. We’d fire up Mosaic or Netscape, type in a URL, and hope for the best. Search engines were in their infancy, and you really had to know your way around to find what you were looking for.

But as more and more websites popped up, it was easy to feel overwhelmed. How could you possibly keep up with all the new sites, let alone know which ones were worth visiting?
There it was, the solution: the web directory page. These handy sites collected and categorized all the URLs you could ever want, making it easy to find what you needed.

🚀 Fast forward 25–30 years and we’re in a similar situation with AI apps. There’s an explosion of new apps, all promising to revolutionize productivity, sales, and everything in between. And just like with those early days of the web, it can be tough to know which apps are worth your time.

But never fear, my friends. Just as the web directory page was the answer back in the day, I recently found “There’s an AI for that” — a directory of all the AI apps you could ever want, filtered and categorized for your convenience.

So go forth and explore!

What is your favorite AI application?

Are you exploring AI applications just for fun or as a part of your job (or as a fun part of your job)?

I have yet to find something good for use in my role as project leader.

Let’s explore 😀

One thing missing for AI to transform the project leader role

I’m blown away by Chat GPT capabilities to generate text for use in articles, help me understand new topics better, summarizing text, etc. Sometimes it feels like it can make sense of everything thrown on it.

However, there is one thing preventing Chat GPT from being useful in my role as project leader.

It is not how the generated text sometimes feels lifeless and flat, that’s most often fine or even appreciated when writing internal company documents.

The information I need is not there, it is not in the model.

Since the model is trained on generic data found on the internet and 80% of the information I need in is internal. It can be found in e-mails, direct messages, documentation, and other internal sources that the Chat GPT model was never trained on.

💡If it was possible to

1. Train a small model on the sources above and append to to the large language model used in ChatGPT, and
2. The small model was retrained frequently (say daily at start),

It will be a complete game changer for me, and I think it will have profound implications on how we work together.

Imagine that we had such a model, then I could…

📌Ask it to write a project plan and include relevant lessons learned from similar projects — it will give me a project plan that follows the company guidelines.

📌Ask it to give me an update on the key deliverables in my project. Most likely this information is available in e-mails, chat-logs and other project management tools, since all of these are included in the model and it knows the basics about the projects, it will spit out exactly the right information.

📌In addition to summarizing the meetings, it will be able to inform us during a meeting, that the last time we spoke about this topic we said… and even loop in information from e-mails regarding certain topics.

The list goes on and on…and on…

I bet that both start-ups and major companies such as Microsoft and Google, are currently tinkering with it. I will hunt for evidence 😊

❓What happens when we see the roll-out of these models?

As project leaders we can either super-power our current methodologies such as Prince II, PMI, SCRUM,… or, more exciting, build new ways of working from the ground up.

❓Imagine that you could get the information you want regarding any project related topic by just typing in the question into a computer interface, how would that change the way you run meetings? Which meetings would be removed? Which meetings would be added?

If we take the leadership perspective, I spend a lot of time trying to create the optimal conditions for my team members to thrive and be successful. If I have a trained model that contains all information from meetings and e-mails, it will be able to help me with this as well. Since the model is also trained on general knowledge (internet), it can help me with suggestions for how to, using validated methods, improve the performance / working conditions for my team members.

❓What would that mean for you as leader? Team member?

Hopefully there will be more time to look my team members in the eyes and ask them how they feel and focus on being human.

There is a paradigm shift at the horizon and we are pretty close to the horizon, buckle up — let’s enjoy the ride.

Where are we now in the hype cyclefor AI?

There is a lot of talk about AI in my LinkedIn flow (I love it), especially about Chat GPT and stable diffusion...

Where do you think we are on the Gartner hype cycle?

FYI -The Gartner hype cycle tracks the journey from the initial spark of innovation to widespread adoption. From excitement to disappointment, to actual value...

The tech hype pass through 5 stages
*Innovation Trigger,
😀Peak of Inflated Expectations,
🤔Trough of Disillusionment,
💡Slope of Enlightenment,
👏Plateau of Productivity.

Curious to hear what you think. 

Chat GPT for project leaders

How will AI tools such as Chat GPT influence my work as project leader?

Well… a lot.

I’m fairly sure that a one-stop-shop for solving the diverse project leader role will not be released soon. AI will increase its usefulness by taking on more and more abstract tasks. I predict that the difference in way of working between 2022 and 2025 will be significantly greater compared with 2019 and 2022. We are about to see a massive change in what we spend our time on doing.

❓How to improve your efficiency?

For someone such as a project leader to increase efficiency (do more in less time with better results) it’s important to be able to clearly define the tasks that are being done. The size and level of abstraction of the tasks must be suitable for the method that is being applied. For example, if you are using a human assistant the tasks can be rather complex and abstract.

What we’re seeing now is that available AI technologies such as chat GPT can be used to take on more and more abstract tasks. Let’s look into this, I think there is already today a lot of help to be gained.

What do I do as a project leader?

The list below is not intended to be complete, but more to give you a feeling for how to start breaking down and categorizing your tasks in the shape of form for looking after solutions.

4. Highly abstract level

• Create a positive team spirit
• Seek consensus with team members and align the team
• Maintain a high-level view on the project
• Manage external and internal relationships
• …

3. Medium abstract level

• Find solutions by using available information found in emails, chat logs, meeting notes, documents, intranet and internet.
• Keep the team and project stakeholders up to date on project status
• Schedule and coordinate resources (including onboarding new project members)
• …

2. Less abstract level

• Read and answer emails
• Push team members to complete tasks on time
• Meetings, schedule, plan and create meeting presentations, facilitate, take notes and distribute, follow up on earlier distributed tasks,
• Create and update project documents such as, time plan, budget, risk register, issue register, document register,…

1. Concrete level

• This involves e.g., taking information from e-mail and pasting it into word, and in many cases, it can be automated using available tools (IFTTT, Zapier,…).

Up until now, us standing outside the inner circle of AI development have been mostly getting help with concrete (level 1) tasks. The release of GPT-3 changed all of that. Now AI technologies are in the hands of everyone and can help on all these levels but the requirement for human intervention is different.

Let’s cherry-pick to illustrate my point.

Take the task of writing meeting notes and summarizing actions, this is something I spend quite a lot of time on. Today the speech-to-text is very good, and it is quite straightforward to capture everything that is being said in a meeting. If you paste the raw meeting capture into a Large Language Model such as ChatGPT, it can easily summarize the meeting and e.g., make a list of actions distributed at the meeting. Thanks 😊

One blocker for applying the workflow above is that many companies do not allow for using external tools with sensitive information. This is in essence already solved, e.g., Microsoft is releasing meeting summary functionality with “intelligent recap” in Teams Premium, and I’m sure that also Google have something similar.

As for all new technologies this is likely to have a few hiccups initially… give it some time and it will do the job better or equally good as humans do it today. Suddenly we can remove one of the time-consuming tasks for the project leader and the available time can be used for working on tasks where human interaction is required and/or run more projects in parallel.

❓What will remain of the project leader when the layers are peeled off?

In the book “Momentum”, Kjell A. Nordström and Per Schlingman conclude that:

The future leader is a storyteller.

That is, focusing on human interaction and abstract tasks and leaving the rest to our AI assistants.

❓What do you think about the future of leadership? What will you spend time on when your administrative work is heavily reduced?

The field of AI moves very quickly and I’m sure that much of the assumptions above are already confirmed 😊 Exciting times.

What makes AI development special?

 💥 Nothing happens on the surface...then boom, problem solved... no human can compete. 

  
I'm all about practical applications of AI and 2022 I got a few "wow" moments and I would like to share one with you now. 
  

👨‍🎓 As a student at Lund University, I remember one of my professors telling a story about the early days of determining the 3D structures of proteins using X-ray crystallography. The output data from the X-Ray machines was printed on several large (square meter) transparent sheets that was hung from the roof, in front of each other in a large room. By looking through all these sheets, it was possible to "see" the 3D structure. As the story goes, there were one guy who had eyes like Marty Feldman which made him exceptionally good at seeing the 3D structure. Complicated stuff. However, it turns out to be worth the effort. 
  
Proteins are the building blocks of all living organisms, and their 3D structure plays a crucial role in how they work. Determining the structure of a protein can provide important insights into how it functions and how it can be used to e.g., develop treatment for diseases. Proteins can also be described with a 1D amino acid sequence, this is quite easy to determine, but not as useful as the 3D structure. Considering that there are more than 100 million proteins known to science, let's build X-ray machines like crazy...or?! 
  
In September 2010 DeepMind was founded, for the wider audience (such as me) the company is most known for beating the world champion in the board game Go. 
  
💥 In the early days they wanted to beat the computer game Pong using their AI algorithms. It took 6 months for the system to score its first point... then it got one point... then it won a game...then it started winning 21-0 and could not be beaten by a human anymore. Boom. 
  
Going back to protein folding (1D to 3D). DeepMind wanted to solve this problem with AlphaFold and so they did. Training their AI on the known 3D protein structures (shout out to experimentalists) resulted in a system that can go from a 1D to 3D in seconds, this with good enough accuracy for practical applications. 
  
Alphafold computed the 3D structures of 20 000 proteins overnight, and in 2022 over a million protein 3D structures was released. What earlier took thousands of man years is now done in less than 24 hours and is accessible for us with normal eyes. Nothing... then boom, the problem is solved, and no human can compete at that specific task. 
  
We will see more and more of these "explosions", I'm curious to see how it will change the (project) leader role, which of my tasks will I be able to hand an AI-assistant with faster and/or better results? I keep my fingers crossed for maintaining the project budget up to date or document management. 
 
What do you think? Which parts of your profession will be disrupted? 
  
*The DeepMind info is from an interview with Demis Hassabis.

Is Chat GPT "smart" enough to be accepted to the university?

Let's see how well it scores on the Swedish university entrance exam ("högskoleprovet").

 

For fun, I put Chat GPT to the test and it got a score of 39 of 70 at the May 2022 exam. If excluding the diagram-based questions, the maximum score is 58, giving Chat GPT a relative score of 67%*. This translates to a normed score of 1.0 (2.0 is the maximum), which beats 70% of the participants and qualifies ChatGPT, as one of the 28 students, for the Economy Program at Örebro University. Congrats!
 
Looking a bit more into details, ChatGPT scored exceptionally well on the Swedish verbal part with a score of 25/30. I was especially impressed with the reading comprehension. It scored worse on the mathematics part, 14/28, which makes sense considering how the model was trained. It is still better than random guessing, and some mathematical "reasoning" was awesome and correct.
 
What does it all mean?
We already see amazing companies emerging using these technologies, e.g., Sana labs and Hypertype. For 2023 even more advanced language models will be released, also a model trained specifically for Swedish.
 
How will this influence my job as project leader?
 
This is a fascinating topic, and we are just at the beginning of what is likely to be the most significant technological advancements of our lifetime. I will devote as much time in 2023 as possible to explore how this can be used for (project) leaders and share my findings.
 
Let's go!
 
*Depending what assumptions are being made, the relative score is between 56% and 67%.