AI for Orchestrators - Newsletter #16

The latest AI insights for Business Leaders and Organisational Orchestrators.

Staccato provocation…

Ever heard of a human hallucinating in a business meeting….?

We often forget that the daily deluge of new capabilities from LLMs and other forms of AI that we get exposed to are things that teams have been working on for a long time. We also must remember how we implementers of AI, are part of the feedback loop that provides developers and entrepreneurs with data on how their products are being applied, not to mention more data for tuning, as well as scaling data from which investors, corporations and governments allocate capital to build out the energy-hungry and thirsty chip-filled data centres to project the flywheel forward.

Phew!

This week we offer up a selection of news items from across the AI spectrum. And, as you scan through the items, consider what maybe converging across different tracks of development and across industries. Consider how the AlphaFold 3 announcements while speeding up drug discovery and clinical trials could be combined with LLM capabilities in the actual running of the company. So you get the scientific aspects accelerating the product side, and the content creation tools bring down the costs and accelerating the revenues and margins of the business. People are already figuring out that by selecting from a broad menu of cheap (relative to pre-Nov ‘22 times) easily accessible capabilities, we can accelerate our endeavours forward like never before. And, as everyone says these days, today’s AI capabilities will only get better…fast.

Same goes when combining robotic learning and simulation with other business-related AIs, which is why we dip our toes into the latest news in that space.

Much to tinker with and consider, as you harness the winds and waves of opportunity. With that said, your time, Dear Orchestrators, is limited, so lets dive into some of the stories that caught my attention in the last week, summarised in the mind map below courtesy of ChatGPT/Whimsical GPT…

This weeks attention grabbers:

• In AI biological news, Google DeepMind and their Isomorphic Labs team announced details on the new capabilities of AlphaFold 3 for “accurately predicting the structure of proteins, DNA, RNA, ligands and more, and how they interact, we hope it will transform our understanding of the biological world and drug discovery.” Watch out for emerging flywheel effects as the research and corporate players start to spin-up, accelerating time to market and the lowering of costs to discover new drugs.

• …and here is Google DeepMind’s Demis Hassabis speaking to Bloomberg about AlphaFold and broader Google AI initiatives. A solid interview worth watching.

• Good insights from Eric Schmidt on CNBC in a wide ranging AI discussion.

• Robots and LLM training news - NVIDIA’s DrEureka is an LLM agent that can help train robots in simulations, bridging the gap between simulations and real-world deployments, saving a lot of time and cost. Interesting Engineering has more including a vid.

• Neuralink 1st patient update on the incredible progress being made.

• Dr Fei-Fei Li gives some good perspectives in a wide-ranging Bloomberg interview on where AI is going.

• AI Music generation - ElevenLabs is previewing its capabilities to generate music from prompts. Those old cassettes (?) will be worth millions once this goes mainstream.

• Bloomberg again and their conversation with Reid Hoffman…human and AI versions.

• Deepfakes via voice cloning on the rise - FT has another story of WPP getting scammed via a Teams call (paywall).

• a16z Podcast - lots in here including current challenges for AI applications at 22:05 .

• Unfortunate…Apple’s iPad ad got a lot of blowback. Watch the vid to understand why…The FT sums it up here (paywall).

Here are 5 questions designed to probe Business Orchestrators on integrating various AI technologies to accelerate productivity and innovation across business functions:

1. Integration Scope: How can we integrate scientific AI, particularly in molecular biology and drug discovery, with language models to streamline our R&D documentation and data interpretation processes?

2. Training Enhancement: What are the potential benefits of combining AI used in robot training simulations with language models to develop training programs that not only train robots but also educate our workforce on AI capabilities and applications?

3. Cross-Functionality: Can language models serve as a bridge to enhance communication between our technical teams working on scientific AI and non-technical teams, thereby improving project alignment and execution speed?

4. Decision Making: How might we employ language models to refine the analysis and presentation of data collected from scientific and robotics AI, thus aiding clearer and faster decision-making processes?

5. Innovation Tracking: What strategies should we consider to ensure continuous learning from our integrations of scientific AI, robotics simulation, and language models, so we can maintain a competitive edge and adapt quickly to new technological opportunities?

…and here’s that in a mind-map, generated in ChatGPT with Whimsical GPT:

Staccato Burst…

More from more….more capability that can be applied to more interesting challenges as a result of the automation of the mundane tasks that consume so many people and organisations with so much potential…

That’s all for this week. If you’re curious you can also check out more insights from The Nordic Bridge on YouTube, on the organisational implications from applying (or not applying) GenAI.