The 2023 book entitled: “The Coming Wave: Technology, Power, and … “ by Suleyman and Bhaskar is a fascinating story of Artificial Intelligence (AI) and biotechnology and how it has and will continue to sweep over humanity in a wave that will improve our lives and change our society in several ways. Of interest to readers will be historical factual stories of past waves of technology and how they have improved live on earth. For those interested in the technical details of AI and biotechnology there is a great deal of informative discussion in an understandable form. Also, there is easy to understand, albeit, somewhat speculative view of what downsides this new wave of technology might portend if not appropriately contained. The book is worth purchasing and reading especially for those interested in the power of technology.
The editors include the following “advance praise” for the book: “The Coming Wave is a fascinating, well-written, and important book. It explores the existential dangers that AI and biotechnology pose to humankind, and offers practical solutions for how we can contain the threat. The coming technological wave promises to provide humanity with godlike powers of creation, but if we fail to manage it wisely, it may destroy us.”—Yuval Noah Harari, New York Times bestselling author of Sapiens.
The authors (Suleyman and Bhaskar) write: “Artificial intelligence (AI) is the science of teaching machines to learn humanlike capabilities... THE COMING WAVE [is about an] emerging cluster of related technologies centered on AI and synthetic biology whose transformative applications will both empower humankind and present unprecedented risks… The coming wave is defined by two core technologies: artificial intelligence (AI) and synthetic biology. Together they will usher in a new dawn for humanity, creating wealth and surplus unlike anything ever seen… it appears that containing this wave—is not… possible.”
The authors write: “I [Suleyman] co-founded a company called DeepMind with two friends… in… 2010. This was our goal… replicate the very thing that makes us unique as a species, our intelligence… DeepMind became one of the world’s leading AI companies, achieving a string of breakthroughs… Today, AI systems can almost perfectly recognize faces and objects. We take speech-to-text transcription and instant language translation for granted… AI systems can produce synthetic voices with uncanny realism and compose music of stunning beauty… AI has been climbing the ladder of cognitive abilities for decades, and it now looks set to reach human-level performance across a very wide range of tasks within the next three years...”
The authors write: “a short time before the onset of the COVID-19 pandemic, I attended a seminar on technology risks at a well-known university… One… presenter showed how the price of DNA synthesizers, which can print bespoke strands of DNA, was falling rapidly. Costing a few tens of thousands of dollars, they are small enough to sit on a bench in your garage and let people… manufacture—DNA. And all this is now possible for anyone with graduate-level training… the presenter painted a harrowing vision: Someone could soon create novel… pathogens far more transmissible and lethal than anything found in nature… This was not science fiction… a single person today likely “has the capacity to kill a billion people.” All it takes is motivation... I stayed silent, frankly shaken… This widespread emotional reaction I was observing is something I have come to call the pessimism-aversion trap: the misguided analysis that arises when you are overwhelmed by a fear of confronting potentially dark realities, and the resulting tendency to look the other way…”
The authors write: “History is full of false prophets and doomsayers proven wrong. Why should this time be different?... Many of those whom I accuse of being stuck in the pessimism-aversion trap fully embrace the growing critiques of technology… We’ll manage, we always do, they say…
Technologies can and should enrich our lives; historically, it bears repeating, the inventors and entrepreneurs behind them have been powerful drivers of progress, improving living standards for billions of us. But without containment… the benefits it could bring, is inconsequential… Scores of state and non-state actors will race ahead to develop them regardless of efforts to regulate and control what’s coming, taking risks that affect everyone, whether we like it or not.”
The authors write: “For most of lived history, proliferation of new technology was rare. Most humans were born, lived, and died surrounded by the same set of tools and technologies… Once a technology gets traction, once a wave starts building, the historical pattern we saw with cars is clear. When Gutenberg invented the printing press around 1440, there was only a single example in Europe: his original in Mainz, Germany. But just fifty years later a thousand presses spread across the Continent”
The authors write: “Civilization’s appetite for useful and cheaper technologies is boundless. This will not change… Computing transformed society faster than anyone predicted and proliferated faster than any invention in human history… Gordon Moore [conjectured]… every twenty-four months, the number of transistors on a chip would double… Since the early 1970s the number of transistors per chip has increased ten-million-fold. Their… power has increased by ten orders of magnitude—a seventeen-billion-fold improvement… It took smartphones a few years to go from niche product to utterly essential item for two-thirds of the planet.”
The authors write: “AI became real for me... It happened in DeepMind’s first office… one day in 2012… We had watched as the algorithm taught itself something new. I was stunned… But the public response was pretty muted. AI was still a fringe discussion, a research area on the margins. And yet within a few short years, all that would change as this new generation of AI techniques exploded onto the world stage… Despite its simple rules, Go’s complexity is staggering. It is exponentially more complex than chess… [The old chess game] approach is hopeless in a game with as many branching outcomes as Go… AlphaGo initially learned by watching 150,000 games played by human experts… the key next step was creating lots of copies of AlphaGo and getting it to play against… itself over and over… Our AI had uncovered ideas that hadn’t occurred to the most brilliant players in thousands of years... with just a day’s training, AlphaZero was capable of learning more about the game than the entirety of human experience could teach it… Our team had, in full view of the public, emerged from what researchers had called “the AI winter,” when research funding dried up and the field was shunned. AI was back, and finally starting to deliver.”
The authors write: “It’s easy to grow weary of the breathless press releases, the self-congratulatory product demos… AI is at the center of this coming wave. And yet, since the term “artificial intelligence” first entered the lexicon in 1955, it… took nearly half a century, finally arriving in 2012 in the form of a system called AlexNet. AlexNet was powered by the resurgence of an old technique that has now become fundamental to AI, one that has supercharged the field and was integral to us at DeepMind: deep learning… A technique called backpropagation then adjusts the weights to improve the neural network; when an error is spotted, adjustments propagate back through the network to help correct it in the future… This, in a nutshell, is deep learning. And this remarkable technique, long derided in the field, cracked computer vision and took the AI world by storm. AlexNet was built by… Geoffrey Hinton [et al.]… Thanks to deep learning, computer vision is now everywhere… we sold DeepMind to Google, and the tech giant soon switched to a strategy of “AI first” across all its products… Starting in the 2010s, the buzz… around AI was back, stronger than ever… Our WaveNet project was a powerful text-to-speech system able to generate synthetic voices in more than a hundred languages across the Google product ecosystem… AI is… far from done.”
The authors write: “in November 2022, the… company OpenAI released ChatGPT. Within a week it had more than a million users
… Ask [ChatGPT] a question and it replies instantaneously in fluent prose… in 2017 a small group of researchers at Google… laid the foundation for what has been… a revolution in the field of large language models (LLMs)—including ChatGPT… LLMs take advantage of the fact that language data comes in a sequential order… OpenAI released GPT-2. (GPT stands for generative pre-trained transformer.)… when OpenAI released GPT-3, that people started to truly grasp the magnitude of what was happening. With a whopping 175 billion parameters it was, at the time, the largest neural network ever constructed, more than a hundred times larger than its predecessor of just a year earlier… When GPT-4 launched in March 2023, results were again impressive… request start-up business plans and the output is akin to having a roomful of executives on call. Moreover, it can ace standardized tests… [and]… identify weaknesses in contracts, and suggest compounds for novel drugs, even offering ways of modifying them… ”
The authors write: “a key ingredient of the LLM revolution is that for the first time very large models could be trained directly on raw, messy, real-world data, without the need for carefully curated and human-labeled data sets… Today’s LLMs are trained on trillions of words. Imagine digesting Wikipedia wholesale, consuming all the subtitles and comments on YouTube, reading millions of legal contracts, tens of millions of emails, and hundreds of thousands of books. This kind of… consumption of information is not just difficult to comprehend; it’s truly alien.”
The authors write: “LLMs aren’t just limited to language generation.
In 2022, OpenAI and Microsoft unveiled a new tool called Copilot, which quickly became ubiquitous among coders. One analysis suggests it makes engineers 55 percent faster at completing coding tasks, almost like having a second brain on hand… It took LLMs just a few years to change AI. But it quickly became apparent that these models sometimes produce troubling and actively harmful content like racist screeds or rambling conspiracy theories… The potential for harm, abuse, and misinformation is real.
Researchers all over the world are racing to develop a suite of new fine-tuning and control techniques… much more is still needed.”
The authors write: “… less well known is what The Economist calls the Carlson curve: the epic collapse in costs for sequencing DNA… the cost of human genome sequencing fell from $ 1 billion in 2003 to well under $ 1,000 by 2022. That is, the price dropped a millionfold in under twenty years… Genome sequencing is now a booming business… But the power of biotech… now enables us to edit it, and write it, too… Impacts can be enormous: editing germ-line cells that form eggs and sperm, for example, means changes will echo down through generations… Experiments that once took years are tackled by grad students in weeks… You can now buy a benchtop DNA synthesizer… for as little as $ 25,000 and use it as you wish, without restriction… at home in your bio-garage.”
The authors write: “Simply knowing the DNA sequence isn’t enough to know how a protein works. Instead, you need to understand how it folds. Its shape, formed by this knotted folding, is core to its function: collagen in our tendons has a rope-like structure, while enzymes have pockets to hold the molecules they act on… in advance, there was no… knowing how this would happen… In 1993, they… set up a… Critical Assessment for Structure Prediction (CASP) [competition] —to see who could crack the protein folding problem… in 2018… a rank outsider entrant arrived at the competition, with zero track record, and beat ninety-eight established teams. The winning team was DeepMind’s. Called AlphaFold, the project… provides a perfect example of how both AI and biotech are advancing… One headline said it all: “One of the Biggest Problems in Biology Has Finally Been Solved,” wrote Scientific American… For half a century protein folding had been one of science’s grand challenges, and then, all of a sudden, it was ticked off the list.”
The authors write: “Soon after the Russian invasion of Ukraine began on February 24, 2022, residents of the city of Kyiv… dismounted near the column’s head and launched jerry-rigged drones equipped with small explosives… The Ukrainian resistance… demonstrated how they can undermine a conventional military calculus... A thousand-strong group of nonmilitary elite programmers and computer scientists banded together in an organization called Delta to bring advanced AI and robotics capabilities to the army… Delta’s ability to create machine learning systems to spot camouflaged targets and help guide munitions was critical… Drones provide us with a glimpse of what’s in store for the future of warfare… It won’t just be… soldiers... It will be anyone who wants to.”
The authors write: “In 2020 an AI system sifted through 100
million molecules to create the first machine-learning-derived antibiotic… To date eighteen clinical assets have been derived with the help of AI tools… What if, instead of looking for cures, you looked for killers? They ran a test, asking their molecule-generating AI to find poisons. In six hours it identified more than forty thousand molecules with toxicity comparable to the most dangerous chemical weapons, like Novichok… Most technologies have military and civilian applications… the more powerful the technology, the more concern there should be…”
The authors write: “Modern research works against containment. So too do the necessity and desire to make a profit… Investment in AI technologies alone has hit $ 100 billion a year… big numbers do actually matter…technologies… will reduce the cost of tactical drones to a few thousand dollars, putting them within reach of everyone… A legal AI might be able to parse this against multiple legal systems, figure out every possible infraction, and then hit that company with multiple crippling lawsuits around the world at the same time.”
The authors write: “Containment is about the ability… to control technology… “what might containment, even in theory, look like?... the answer… Deft regulation, balancing the need to make progress alongside sensible safety constraints… We’ve done it before, so the argument goes; look at cars, planes, and medicines… [In] CHAPTER 14 [the authors provide] TEN STEPS TOWARD CONTAINMENT”
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Reviews with images
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Everyone should know what’s coming with AI - best read of the year with clear insights from industry insider
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