The AI Conversations That Shaped 2023

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Looking Back at the AI Conversations That Defined 2023

To close out 2023, I thought it would be interesting to look back at some of the major AI-related topics that defined the year. Topping the list would be the surprise ousting and subsequent return of Sam Altman as CEO of OpenAI, which sparked heated debates around ethics and governance in the AI community.

2023 saw artificial intelligence (AI) and machine learning (ML) advance rapidly, sparking vibrant discussions within developer communities and the technology press. Key discussion topics from these spheres offer a glimpse into the pivotal issues shaping AI conversations this year.

Developer forums centered heavily on cutting-edge techniques, infrastructure, and applications to push new frontiers in AI capabilities. Key topics included neural networks, foundation models, and most notably, large language models like GPT, Llama, and Claude. Ethical considerations around responsible AI development received some attention, but business applications took priority. Developers are super excited about GenAI and LLMs, many are experimenting with tools, frameworks, and many are starting to build simple apps. 

Developers also grappled with the immense resource demands of training these large models, exploring cutting-edge hardware and cloud solutions. But the focus wasn’t just on pre-training and fine tuning; deploying AI solutions into the real world was equally critical. Frameworks and tools for integrating AI into existing systems dominated discussions, reflecting developers’ desire to translate their creations from prototypes to practical solutions.

Over the past year, technology media coverage has transitioned from an intense focus on cryptocurrency and web3 to highlighting rapid advancements in AI. During this shift, many journalists and outlets have aimed to provide measured perspectives on AI, underscoring its transformative possibilities as well as ethical considerations. While publications explored the diverse applications of AI across industries, from streamlining business operations to revolutionizing art and entertainment, concerns about the proliferation of “deepfakes” and misinformation cast a shadow on this progress. However, they also acknowledged the persistent limitations of current AI systems, particularly around interpretability and potential biases in decision-making. As public interest grew regarding AI’s broad societal impact, corporate AI strategies and the broader implications of this technology gained significant media traction, reflecting a desire for a deeper understanding of where rapid advancements in AI may lead us.

Together, these snapshots reveal a rapidly evolving domain working on cutting edge breakthroughs yet also grappling with complex questions around ethics and governance. As AI advances continue reshaping industries and society in 2024, sustained collaborative dialogues between developers, policy makers, domain experts and the public will remain vital.



Data Exchange Podcast

1. Knowledge Graphs: Contextualizing Enterprise Data for More Accurate LLMs.  Juan Sequeda and Dean Allemang are knowledge graph experts at data.world, and co-authors of a recent Text-to-SQL benchmark involving LLMs and knowledge graphs.

2. Democratizing Wealth Management With AI.  Chirag Yagnik is a co-founder of Arta, a compelling new startup that harnesses innovations in artificial intelligence and software to develop wealth management solutions.


Unlocking the Power of Incentives: 2023 Book of the Year

In the fast-moving worlds of artificial intelligence, machine learning, and data science, truly understanding user behavior and motivation is the key that unlocks innovation and progress. This is why Gradient Flow is happy to name economist Uri Gneezy’s Mixed Signals our 2023 Book of the Year 🏆

Weaving together insights from psychology and economics, Gneezy creates a practical framework for designing incentives that shape behavior. His exploration of both monetary and non-monetary motivations offers interdisciplinary insight, enriched by captivating examples that range from the animal kingdom to complex modern organizations.

For technologists, the book reveals how incentives act as signals that influence decisions and markets. By aligning incentives with goals and ethical values, innovators can enhance products, optimize algorithms, and avoid unintended consequences. For business leaders, Gneezy’s taxonomy of incentives and emphasis on credibility provides the tools to motivate teams, excite customers, and drive results.

Mixed Signals transcends disciplines by seamlessly translating academic concepts into easily accessible and applicable advice. Gneezy’s clear prose and engaging anecdotes make the book entertaining as well as useful. Readers emerge with an elevated perspective on human dynamics and a refined understanding of how strategic incentives can overcome mixed signals.

As we face complex problems, bringing out humanity’s best is vital. Uri Gneezy’s ‘Mixed Signals’ offers technologists and leaders insights to drive positive change. By exploring the complex motivations behind human behavior, this thoughtful book helps unlock our potential to improve society.


From Financial Machine Learning: A Cheat Sheet

Here’s another worthwhile read for the holidays 🎄 Peter Turchin’s thought-provoking new book End Times  insightfully applies data science techniques to examine the intriguing question of whether societies collapse in predictable cycles. Drawing on the emerging field of cliodynamics, which models historical trends as complex systems, Turchin foresees a coming age of discord driven by worsening inequality and elite overproduction.

While not a typical analytics read, End Times will resonate with anyone interested in using data to understand complex human behaviors. Turchin utilizes demographic data, social network analysis, and dynamical systems modeling to test the structural-demographic theory on the rise and fall of empires. His interdisciplinary approach incorporates elements of operations research, complexity science, and agent-based modeling.

The book’s data-driven arguments and wealth of historical analyses make for an engaging examination into the mathematically predictable forces behind societal instability. As AI/ML permeates business and policy decisions, Turchin’s warning on projecting the unintended consequences of new technologies is prescient. 


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