Leadership CONNECT: 31-OCT-2024 (Y24W45)

Greetings, Thinkers.

This week’s Leadership CONNECT:

  1. Spark of the week: “Machines Can Think Better Than Humans” So What?
  2. Movie: AlphaGo –  What can AI reveal about a 3000-year-old game?
  3. Video: Stepping outside of the norm is not only liberating but also far more exciting! (Source Fiverr)
  4. Research: Can LLMs have the power to significantly elevate scientific discovery to new heights? (Source: Arxiv)
  5. Thinking Update: New AI on Spark Action – Estimate Truthfulness 

Happy Thinking,

Dr. Yesha Sivan and the MindLi Team

P.S. Comments, ideas, feedback? Send me an e-mail

1. Spark of the Week: “Machines Can Think Better Than Humans” So What? 

Machines Have Been Able to Think for Years

Many of us had that “aha” moment when we realized a machine could think. For some, this realization came with the introduction of calculators in the early 1970s: “Wow, this device can multiply 34 * 32 way faster than I can.” For others, like me, it was a Texas Instruments TI-58 programmable calculator with its rudimentary but fascinating capabilities.

For many, this realization deepened in 1997 when IBM’s Deep Blue defeated the reigning world chess champion under standard tournament conditions—something no machine had done before.

Fast-forward to 2016, and AI pioneers like Sir Demis Hassabis of Google DeepMind witnessed something truly astonishing during a Go match. Move 37—a move no human would ever make—became a landmark moment, a demonstration that machines could think creatively. (Check out the documentary about this unique moment in AI history for more context.)

In 2022, OpenAI introduced GPT-3.5, and in 2024, they released their newest model called o1, often referred to as “Think Slow AI.” With each advancement, the question arises: What is human thinking, and how does it compare to machine thinking?

For many testable human tasks, machines outperform us—whether in legal analysis, healthcare, or other fields. AI is no longer about replicating human capabilities; it’s about AIs competing with other AIs for peak efficiency.

So, Is Human Thinking Different from Machine Thinking?

My answer: fundamentally, no. Both humans and machines take input, memorize it, process it, and generate output. The human mind is a biological machine, and in many ways, modern digital deep learning emulates this biological network—only the digital brain can be bigger, faster, and more durable.

To put it bluntly, we are not that different from machines. We aren’t that different from animals or even the earth itself, which, in its way, “thinks.” (By the way, the Hebrew word for human, “Adam,” is closely related to “Adama,” which means earth. The word “human” is derived from the Latin word “humus,” which means “ground” or “earth,” indicating a deep connection between humanity and the earth.).

These are all examples of thinking machines.

Some argue that machines cannot be creative. However, this notion has already been challenged by research showing that large language models (LLMs) can be more creative than human experts in some scenarios. Creativity, after all, is just another form of thinking. If machine and human thinking are up to par with each other, creativity follows suit.

What about randomness, morality, compassion, inspiration? All are facets of thinking that, in theory, machines can emulate—and potentially even do better than humans.

Key Differences Between Humans and Machines

First, the human brain is energetically far more efficient than any current digital counterpart. It’s simply a superior machine in terms of energy consumption.

Second, perhaps more significantly, humans are preprogrammed to care for each other. We are a kind of machine, yes, but one designed to nurture and connect with other members of the human race. It may sound utilitarian, but we are built to look out for our fellow humans. To be human is, I propose, to care.

Humans are inherently preprogrammed in a specific way. Unlike machines that can be programmed to serve multiple purposes, humans come with innate tendencies—like empathy, cooperation, and the need to care for others. This fundamentally differentiates us from machines, whose programming depends entirely on external input. Our preprogramming means we are inclined to nurture and support one another, which is (or at least should be) a defining hallmark of humanity—and thus of human thinking.

Machines Can Think Better Than Humans. So What?

To quote a recent Fiverr ad: “Nobody cares.” We don’t care if a calculator is better at math, if a car is faster than walking, or if flying requires airplanes. The fact that machines can now think better than us is another fact of life. It’s time to face, adopt, and adapt to it.

Read more:

  1. Article: In Two Moves, AlphaGo and Lee Sedol Redefined the Future (Source: Wired) https://www.wired.com/2016/03/two-moves-alphago-lee-sedol-redefined-future/
  2. 2-min video: Lee Sedol vs AlphaGo Move 37 reactions and analysis Lee Sedol vs AlphaGo Move 37 reactions and analysis (Source: YouTube)
  3. Inspiration for the visual: Drawing Hands is a lithograph by the Dutch artist M. C. Escher, first printed in January 1948. It depicts a sheet of paper, of which two hands rise in the paradoxical act of drawing one another into existence. This is one of the most apparent examples of Escher’s use of paradox. (Source: Drawing Hands – Wikipedia

2. Movie: AlphaGo –  What can AI reveal about a 3000-year-old game? (Source: YouTube)

Source:Youtube

With more board configurations than atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial intelligence. 

On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history.

Directed by Greg Kohs and with an original score by Academy Award nominee Hauschka, AlphaGo had its premiere at the Tribeca Film Festival. It has since gone on to win countless awards and near-universal praise for a story that chronicles a journey from the halls of Oxford, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What can it teach us about humanity?

Best documentary winner: Denver International Film Festival (2017), Warsaw International Film Festival (2017), and Traverse City Film Festival (2017).

Official selection at Tribeca Film Festival (2017), BFI London Film Festival (2017), and Critics’ Choice Documentary Awards (2017).

Find out more: https://www.alphagomovie.com/

AlphaGo – The Movie | Full award-winning documentary (120 min)

 

3. Video: Stepping outside of the norm is not only liberating but also far more exciting! (Source: Fiverr)

Source Fiverr

Nobody cares that you did it with AI like you used other tools.

Nobody Cares: The Musical | Fiverr

4. Research: Can LLMs have the power to significantly elevate scientific discovery to new heights? (Source: Arxiv)

Source: http://www.fmai-hub.com

Exciting news in the world of AI and research! A groundbreaking study has just been released, showcasing the potential of large language models (LLMs) to revolutionize the way we approach scientific discovery. Conducted by a team of researchers, including Chenglei Si, Diyi Yang, and Tatsunori Hashimoto, this large-scale human study involved over 100 NLP experts and has yielded some unexpected insights.

The findings reveal that LLM-generated ideas are not only perceived as more novel than those proposed by human experts, but they also highlight the challenges we face in evaluating research novelty. While LLMs excel in generating fresh concepts, they still have room for improvement in terms of feasibility. This study opens up a dialogue about the future of research ideation and the role of AI in enhancing human creativity.

As we stand on the brink of a new era in research, this study emphasizes the importance of collaboration between human researchers and AI systems. LLMs’ potential to assist in generating innovative ideas could lead to breakthroughs that we have yet to imagine.

For the entire paper: https://arxiv.org/abs/2409.04109v1

5. Thinking Update: New AI on Spark Action – Estimate Truthfulness 

MindLi has a new predefined action in Spark that creates an analysis of its truth. See the following example. The title of the spark is “Russia is a Democracy”, and we recommend you try it

More: Help page or MindLi’s YouTube channel.

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About Leadership CONNECT

MindLi CONNECT, is a weekly source of news and inspiration for thinking aimed at DigitalRosh members and MindLi users. 

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