2023 was all about GenAI after ChatGPT entrance late 2022: Generative AI: The technology of the year for 2022 Yay for GPT-3 !

In all the avalanche of GenAI news, loved the wit as ever NewYorker’s analysis and experiment in My AI writing robot. Fully human-written text would be a luxury; with AI writing on their own, “only historians and other specialists will be obliged to learn reading and writing in the future”. My favorite human piece: “At times Robot Kyle felt like an extremely enthusiastic & productive, but rarely on-target, personal intern.”

Experiencing the Toronto Internaional Film Festival for the first time, my favorite movie was Robot Dreams: a dog + a robot + New-York in the 80’s in an animated movie, what’s not to love!

Also loved MIT Tech review and how Robots that learn as they fail could unlock a new era of AI Lerrel Pinto says the key to building useful home robots is helping them learn from their mistakes. We can all relate to that.

PRODUCTIVITY & SKILLING

Indeed Frobes, AI is a people problem, not an IT problem: Why The CHRO Will Be The New Boss Of Generative AI

Arstechnica highlighted Goldman Sachs research: productivity boom would eventually raise annual global GDP by 7% over 10-year with Generative AI set to affect 300 million jobs across major economies.

And HBR rightfully predicting that AI Prompt Engineering Isn’t the Future Yes in the age of AI what makes us human is the skill of the future! Not prompt enginnering but problem formulation — the ability to identify, analyze, and delineate problems. Problem diagnosis, 5 Whys, reframing, critical thinking anyone?

USE CASES because as much as I love robots, the business use cases for AI are my jam. Beyond the hype, I love reading about use cases and business impact per industry like this rather than celebrate tech for tech sake.

• Here examples in farming, news media, energy, manufacturing, government, transport, FSI  & retail from The Guardian: from retail to transport, how AI is changing every corner of the economy
• Create Winning Customer Experiences with Generative AI
  • Tech in itself doesn’t create value. The value creation comes from a LLM solution to unmet need, understanding the pain points in  the Customer Experience. 3 core recommendations from HBR:
    1. Focus on the Customer, not the technology: a. recognize the customer need, b. translate these needs into a request and c. respond back to the customer
    2. Focus on the Learning: repeat (this is your feedback loop)
    3. Use technology to complement your capabilities, not substitute for them
• Great use cases and early watchouts from McKinsey
  • Generative AI is here: How tools like ChatGPT could change your business:
    • Where does it aid/disrupt our industry / value chain?
    • What are our policies and posture? Wait to see how the technology evolves, pilot, build a new business? Should the posture vary across areas of the business?
    • What are our criteria for use cases selection?
    • How do we build an ecosyst of partners, communities and platforms?
    • What legal and community standards should these models adhere to for us to maintain trust with our stakeholders?
  • Here Generative AI + Fashion… so many applications for innovation, creativity and business productivity across functions
  • The economic potential of generative AI: The next productivity frontier: Unsurprisingly poised to transform roles, boost performance across Customer operations, Marketing & sales, Software engineering and R&D
  • scWinning in telecom CX: Digital natives redefined customer expectations. Incumbent telcos can rise to the challenge with customer-led CX transformation:
    1. End-to-end redesign of service delivery
    2. New business insights enabled by data, analytics, and AI
    3. Refined commercial model to capture new CX-generated value
    4. Broad cultural transform”ation and investment in frontline CX capabilities
• Bain’s advice to Telcos, Stop Debating Generative AI and Just Get Going: “Applying generative AI to knowledge management is a no-regrets move under any circumstance for telcos (…) because it can create immediate value across business functions.” Love the important realisation too of needing to train teams on #ResponsibleAI

SCIENCE & TECHNOLOGY in 2023

Why neural net pioneer Geoffrey Hinton is sounding the alarm on AI on MIT Sloan: “And if [AI models] are much smarter than us, they’ll be verygood at manipulating us. You won’t realize what’s going on. So even if they can’t directly pull levers, they can certainly get us to pull levers. It turns out if you can manipulate people, you can invade a building in Washington without ever going there yourself.”

Physicist Max Tegmark says competition too intense for tech executives to pause development to consider AI risks. Tegmark wrote a landmark letter in March 2023 calling for a pause in AI development to fully understand the dangers “[it] had more impact than I thought it would” with the political awakening on AI: the US Senate hearings with tech executives, the UK convening aglobal summit on AI safety

The doomers and gloomers: Why AI Will Save the World – Marc Andreessen from A16Z vs on Wired The AI-Powered, Totally Autonomous Future of War Is Here

How AI is learning to read the human mind: The “MinD-Vis” AI model from a research team in Singapore read and reconstruct images from our minds; this is fantastic for patients but mental privacy & “brain rights” are needed to prevent decoding a person’s brain activity without consent. This is a new form of human rights.

When AI Is Trained on AI-Generated Data, Strange Things Start to Happen: “Loops upon loops.” Synthetic data with loops upon loops leads to MAD (Model Autophagy Disorder), like mad cow disease. The solution is to keep watermarking ON.

From the Scientific American Artificial Intelligence Could Finally Let Us Talk with Animals In 2017, 2 research groups discovered a way to translate human language without the need for a Rosetta stone by turning semantic relations between words into geometric ones. ML models are now able to translate between unknown human languages by aligning shapes using the frequency with which words appear near each other to predict what comes next. “The door has been opened to using machine learning to decode languages that we don’t already know how to decode”

10 breakthrough technologies 2023 from the MIT Technology Review:

1. CRISPR for high cholesterol
2. AI that makes images
3. A chip design that changes everything
4. Mass-market military drones
5. Abortion pills via telemedicine
6. Organs on demand
7. The inevitable EV
8. James Webb Space Telescope
9. Ancient DNA analysis
10. Battery recycling

CES 2023 5 AI takeaways from CES for enterprise business:

1. AI at the edge: autonomous robots, agricultural machine for sustainable farming, advanced mobility app, smart home
2. An AI tipping point for marketers, part of their day to day workflows
3. AI & data governance & IoT
4. Conversational AI even more integral to Customer Experience
5. AI & ML everywhere at CES

The 2023 MAD (Machine learning, AI & Data) landscape and “state of the union” of the data and AI ecosystem is here, after a break in 2022

Fantastic 26min summary of Dr John Maeda SXSW 2023 talk on Design in Tech Report 2023: Design and Artificial Intelligence. Always so insightful, thank you for making it available.

Stanford’s 2023 AI Index Report – measuring trends in AI:

• Industry continues to be ahead of academia
• AI help & harm environment
• Is AI the world’s best new scientist?
• Misuse of AI rapidly rising
• AI-related professional skills increase in every US industry sector
• Year over year AI private investment decrease
• Chinese citizens positive about AI products & services

HOW WE CLOSED 2022

8 times scientists exceeded expectations in 2022 – thank you science and The NewYorker for reporting:

1. We Nudged an Asteroid
2. Magic Mushrooms Reduced Depression
3. Earth Got Hotter & Hotter
4. Brain Cells in a Dish Played Pong
5. Ethereum Reduced Its Energy Use by 99.95% aka The Merge
6. We Found 2M year-old Mastodon DNA
7. AI Learned Diplomacy (CICERO)
8. We Generated Fusion Power

What to expect from AI in 2023: 

1. More (problematic) art-generating AI apps
2. Artists to opt out of data sets
3. Open source and decentralized efforts
4. Incoming regulations like EU’s AI Act
5. Investments aren’t a sure thing

HBR’s What companies need to know before investing in AI

• ask if they really need AI
• pick a task not a project to start with
• identify data & complementary systems it will require
• adjust expectations around accuracy
• do not rush to deploy enterprise-wide
• be realistic whether you have the skills to maintain AI
• decide if returns outweigh costs

(Nov 2022 hi, tech No. 140:)🔮 GPT-4 – What to Expect: As with all the fears surrounding new technology, 100% yes to asking better questions Eg. Will we really need Google Search to crawl a load of B2B blogs for content if GPT-4 can give us better answers, faster and tailored to our exact needs? Bing is already working with DALL-E to incorporate AI images into search and that seems sensible.

Authentic leadership means different things to different people. A great definition on FastCo: Leaders who show their real and genuine selves to others at work (that builds stronger bonds of trust); are true and acurate and seen as original. And, yes why We need authentic leadership more than ever in 2022. Still feels so relevant for 2023!