AGI is not a singular, monolithic endeavor, but rather a complex interplay of advancements across multiple technological and scientific domains. And so, while AGI is likely to follow its own combined S-curve over time - the multi-dimensional nature of AGI progress suggests that its emergence will likely be the result of numerous S-curve advancements in various fields, each progressing at slightly different rates and phases"

I couldn’t agree more. Once we accept this we can 1/focus on the great tools we have in LLMs and use them where they shine and 2/ focus on developing additional technical capabilities.

Just stumbled over this gem during my lunch break. We all have been impacted by GenAI wave in the last 20 or so month - Either riding or avoiding the wave. In her talk at Goto Amsterdam conference, Jodie Burchell, PhD, gave a very comprehensive breakdown on the history of LLMs, how they work, what are their intrinsic limitations and where they shine. Highly valuable talk which comes highly recommended - Maybe your next lunch break? (I share the link to the talk page containing video & slides in the comments below).

⏰ Early start and back to Zürich Airport! 🛫 Some disturbances grounded me here last night, but I’m looking back to yesterday’s amazing Generative AI hackathon with a smile 😊.

☕ The participants were very engaged and built impressive PoCs in no time. My favorite feedback was: “It’s amazingly easy to create an 80% solution in almost no time”, “Based on the learning I built a 2nd use case in just 10 more minutes and got amazing results”, and “It’s not just the Generative AI models, but the platform that allowed me to build RAG-based solutions so easily”. 🙌

What a great evening yesterday at the AWS User Group Munich. The quote of the evening for me, yeah I might be a little biased 😉 , was :

“There are multiple model launches in Amazon Bedrock. Launching new models in Bedrock became like new minor versions numbers for databases or other services. Hard to keep up with the pace”.

Reflecting on this, I think that is a very true statement. It underlines the pace of innovation in this space and the necessity of choice at your hands if you want to build #GenAI based application for your customers. Hence the need of a service like #AmazonBedrock. Also featured the Bedrock Converse API, which makes switching models even easier.

How do you choose the foundation model for your Generative AI App — like your car?

Just published a new blog post on medium:

😎 How do you choose the right foundation model for your Generative AI app? 💡 It’s like picking the perfect car!  🚗 Just like car buyers care more about features, price, and user experience, Generative AI app users prioritize functionality, cost, and ease of use over the specific model under the hood.  👷‍♂️ Building a successful Generative AI app requires a well-architected, cost-effective solution that meets customer needs, not just chasing the latest, most powerful model.  🧠 Models are crucial, but they’re just one component. A robust architecture with components like data management, model orchestration, and user interfaces is essential.  💰 Cost-effectiveness matters. Choose the “Goldilocks” model that’s good enough for your use case, not overpowered (and overpriced).  ⏱️ Models evolve rapidly. Your app architecture and processes must allow seamless model updates or replacements to stay competitive.  🧩 Embrace model composability. Use different models for different tasks within your app for optimal cost and performance.  🛣️ Just like cars, Generative AI apps aren’t one-size-fits-all. Tailor your solution to your specific use case and customer needs.  🚀 Don’t get caught up in the hype. Work backward from customer problems to build fantastic, innovative solutions with Generative AI.  🎉 Enjoy the ride and have fun building your Generative AI app! It’s an exciting journey ahead.

What a very looong weekend in Stockholm. Loved every second of it. Started of with spectating the #StockholmMarathon. Would have loved to join, but no last minute (literally) bibs available. Only learned about it in the hour before the start. Still had a very good time.

We started the week with a Prompt Engineering on #AmazonBedrock workshop leading participant through the implementation of a marketing use case. Was great to see Oliver Möller, Tobias Nitzsche and Chakkree Tipsupa in joined action. The workshop has been good received and AWS office’s in Stockholm have been a very welcoming place for all the customers.

👩‍💼LinkedIn is a business network and I will keep it like this. Avoiding personal and political stuff as much as possible. People following me on LinkedIn, will recognise based from the bag and shoes, that I’m on my way to a bigger event. While I’m super thrilled about this, this is not the point of this post. You also see an envelope. The German, a little old fashioned, way for voting in absence. 
🗳️My European friends, the upcoming 2024 EU Election are next weekend, 6-9th June. In Germany you even still have time to opt for the post mail vote. I’m not advertising any political party here, but please make sure that you make your vote. Not voting is equivalent to vote for a party you actually don’t want to support. I know it is not easy, but this is not the time for slack. 
 😎As this anyways is more of a personal note: I’m super thrilled that my oldest is eligible to vote, can take the fate of his own generation in his own hands. But he also needs some support to do so. So parents, being a good example and provide a helping hand really counts here.

Thank you!

Prompt Engineering is possibly the single most valuable skill you have to master if you want to get to production with your Generative AI based application.

As many customers are working hard towards bringing their ideas and proof of concepts to realisations in 2024, this topic hits the keynote stage of the #AWSSummit in Stockholm.

We bring:

• 🛠️a toolbox of proven tools to build reliable prompts
• 👷a mechanism to create reliable results, turning trial&error into engineering
• 📊a ton of learnings from idealo internet GmbH ‘s journey into production

Looking forward to meet you there 😊

The ones who joined Philipp and me in our session at the #AWSSUMMIT in Berlin last week already got a preview of the blog post as we run it as a demo. Nice that it is now published and you all can get hands on it. Kudos!

AWS Inferentia2 is a great way to optimize the inference part of your (gen)AI workloads on AWS and the blog post helps you to dive straight into deploying a LLM (in this case Meta’s Llama 3) model. But it is not “just” Llama 3. From Hugging Face recent blog post: “Enabling over 100,000 models on AWS Inferentia2 with Amazon SageMaker” - https://lnkd.in/ePYb6TFs. So there is a good chance that you can benefit from AWS Inferentia 2 today :)

🦄 I’m super thrilled by Anthropic’s blog post “Mapping the Mind of a Large Language Model”(https://lnkd.in/dA6Jh_pg). On their way to turn the black box into a little bit more transparent and getting a better understanding how state-of-the-art LLMs are working. Interestingly, but not really surprising, that similar methods like are used for exploring human brain activities are providing insides.

🌟 Like always there are flip-sides, but I’m with Anthropic. There are easier ways to create harm and personally I think better understanding of technology will be beneficial.