From AAA to OOO: The NeoMarketing Revolution (Part 4)

NeoMails: Building Brand Hotlines

I asked Claude and ChatGPT to summarise my writings on the three innovations.

Every brand faces a critical engagement challenge: despite collecting customer emails and phone numbers, they lack reliable ways to reach them on demand. Traditional push channels struggle with inbox overload, message fatigue, and rising costs. The result? Brands turn to expensive retargeting through adtech platforms just to reach customers already in their databases.

NeoMails reimagines email as an interactive engagement platform. By creating predictable 15-second daily touchpoints, NeoMails transform random interactions into habitual engagement and build consistent customer connections.

Problems NeoMails Solves

  • The “No Hotline” Crisis: Traditional emails fail to create reliable engagement. NeoMails establish consistent, daily touchpoints that act as dependable “hotlines” for communication.
  • Low Open and Click Rates: By offering value-driven, interactive content, NeoMails turn emails into a source of enrichment, boosting open rates and engagement.
  • Inefficient Reacquisition Spending: Continuous, meaningful contact reduces reliance on expensive reacquisition campaigns via adtech platforms.

How NeoMails Work

Four key elements power NeoMails’ transformation:

  1. Atomic Rewards (Mu) in Subject Lines
    • Gamifies email with points directly displayed in the subject line (e.g., “μ50 inside”).
    • Builds habits and drives anticipation for opening emails.
    • Rewards consistent engagement with micro-incentives.
  1. Micro-Moments of Value
    • AI-generated personalised content that entertains and educates.
    • Interactive elements to capture attention and gather insights.
    • Scheduled daily delivery to establish a ritual and focus on user enrichment over promotion.
  1. SmartBlocks for Engagement
    • Interactive containers within emails for seamless preference sharing.
    • Progressive profiling through daily interactions.
    • Frictionless zero-party data collection to enhance personalisation.
  1. ActionAds for Monetisation
    • Enables in-email transactions without requiring clickthroughs.
    • Features relevant offers from complementary brands.
    • Generates revenue through attention-driven precision targeting using PII-based data.

The Magic of 15 Seconds

NeoMails are designed like the comics page in a newspaper—a daily ritual that delivers value through micro-experiences:

  • A beauty brand shares skincare tips.
  • A financial service offers investment insights.
  • A fitness brand provides quick workout suggestions.

These brief interactions build a habit of consistent engagement.

Zero Cost and Effort, Maximum Impact

For brands, NeoMails operate on a ZeroCPM model:

  • No upfront email-sending costs.
  • AI-driven content creation and automated delivery.
  • Revenue-sharing from ActionAds.

Building the Hotline

NeoMails foster trust and engagement through consistent, valuable interactions:

  • Customers expect and value daily touchpoints.
  • Personalisation improves through collected zero-party data.
  • Attention becomes a monetisable asset, eliminating reliance on costly reacquisition.

The Bigger Picture

NeoMails aren’t just better email marketing—they represent a fundamental reimagining of customer engagement. By establishing direct, reliable hotlines between brands and customers, NeoMails deliver:

  • Lower acquisition costs.
  • Higher engagement and retention rates.
  • New revenue streams.
  • Deeper, more meaningful customer relationships.

NeoMails lay the foundation for shifting from endless acquisition to lasting engagement, reshaping how brands connect with their audiences. This virtuous cycle of trust-building and actionable insights empowers brands to reclaim ownership of customer relationships, reduce inefficiencies, and drive sustainable profitable growth.

Thinks 1493

Kurt Gray: “Bearing in mind that our species is by nature more prey than predator is a good rule of thumb when interacting with people — and it could help soothe today’s intense political animosity by increasing our sympathy for the other side. Just as you vote to protect yourself and your family, so do those who vote differently. The next time you feel angry at your political opponents, pause to think about how they might feel threatened…Unless they see you as naïve, your political opponents probably view you as a predator. To help them understand your true motivation, consider explaining how your beliefs relate to your fears and your desire to protect yourself, your family, your community. You might start a political conversation by asking, “What worries you most about the future?” or “What makes you feel threatened?””

Gautam Mehra: “The gold standard [in data]: deterministic observed data. This is the data of real actions—what people actually do, not what they claim to do or what we approximate they might do. Whether it’s purchase patterns, digital interactions or footfall data, deterministic observed data provides a concrete and unbiased view of reality…the gold standard: deterministic observed data. This is the data of real actions—what people actually do, not what they claim to do or what we approximate they might do. Whether it’s purchase patterns, digital interactions or footfall data, deterministic observed data provides a concrete and unbiased view of reality.”

Raghuram Rajan: “What is important is [India’s] economy itself is not creating enough jobs. Manufacturing, for example, is becoming much more capital intensive over time. Where we are creating jobs is in construction and agriculture. Construction, of course, because of the boom in infrastructure spending, etc, is understandable. Agriculture is worrisome. Why are people going back to agriculture when, in fact, in every developing country, they should be coming out into the services and manufacturing. Services was creating jobs, but through the pandemic, it has not. I think the big question for the government has to be: How do we create more jobs and higher quality jobs?”

The Generalist: ““Startups need to force a choice, not a comparison.” That’s something that Mike Maples told me recently. If a startup forces a comparison, it will inevitably lose because the incumbent can just RFP you to death with incremental features. You can’t come in and say, “Hey I’m building a CRM with a more elegant workflow.” You have to deliver a value prop to your users that is orthogonal in some way – something that is so different from the current offering: like a CRM that doesn’t require data entry, Uber versus taxis, or Gong versus Salesforce. It should be something that’s essentially impossible for the incumbent to react to because you’re changing the conversation, and what was once their strength becomes a kind of weakness. Mike gave the example of Airbnb versus traditional hotels. The Four Seasons has a standardized, cookie-cutter style that lets you know when you’re stepping into one, wherever you are. What Airbnb had was uniqueness – being at an Airbnb in Paris is not the same as being in one in San Francisco or Los Angeles. It forced a choice: Do you want a consistent hotel stay or to experience the city? People will pick different things, which is fine, but you need to appeal deeply to some narrow subset, not try to build the slightly better Four Seasons.”

NYTimes on Mel Robbin’s new book “The Let Them Theory”: “If you stop trying to manage other people’s opinions, actions and moods, then your well-being and relationships will improve. Friends hanging out without you? Let them! Relatives griping about you? Let them! Your date ghosts you? Let them! Don’t stress about what you cannot control; focus on what you can…The first half of the “let them” idea is about freeing yourself from the burden of trying to manage other people. As for the second half, Robbins turns to another concept: “let me.” It goes like this: after releasing what you cannot control, you say “let me” and take responsibility for your next steps. Without that idea, you run the risk of simply shutting down and isolating yourself, the book warns.

From AAA to OOO: The NeoMarketing Revolution (Part 3)

From AAA to OOO

Modern marketing’s excessive dependency on Big Adtech for traffic stems from a fundamental failure: the inability to build deep relationships with existing customers. Even as marketers obsess over AOV, frequency, and repeat purchases, they ignore the root causes – lack of reliable hotlines to customers, and inability to understand them as individuals. Unable to bring their own customers back to their properties for transactions, they become trapped in an expensive CAC game to meet revenue targets.

This is where NeoMarketing comes in.

NeoMarketing is a revolutionary framework that transforms how brands engage with customers in the digital age. It replaces today’s wasteful acquisition addiction (AAA – acquire, acquire, acquire) with a more sustainable approach built on acquiring customers Only Once and treating them as Ones (OOO). Through this paradigm shift, brands can redirect billions in AdWaste toward building lasting, profitable customer relationships while enabling true N=1 personalisation at scale.

I explained the Only Once theory in an essay: “[Only Once’s] core principle is radical yet simple: brands should pay for customer acquisition exactly once, then pivot entirely to relationship building. Paying to reach your own customers repeatedly isn’t just a marketing mistake – it’s a cardinal sin that erodes profitability. The solution requires a complete reimagining of the marketing funnel. Instead of endless acquisition cycles, brands need a dual focus: precise, targeted first-time acquisition, and robust retention strategies that make reacquisition unnecessary…By acquiring right and retaining for life, companies can break free from the costly cycle of endless reacquisition, redirecting millions in wasted ad spend toward building lasting customer relationships.”

To this, I added the “Ones” principle to include N=1 personalisation: “Every marketer dreams of the perfect customer interaction: delivering exactly the right message, at precisely the right moment, through the ideal channel, to each individual customer—creating a virtuous cycle of repeat purchases and maximised lifetime value. Whether called relevance or recommendations, the goal is to eliminate friction and waste in every customer relationship. Yet today’s marketing reality is built on “brand spam” that abuses the trust and permission customers grant. The inevitable result? Customers withdraw their attention and sever connections, forcing brands into a costly cycle of reacquisition through adtech platforms. The ultimate irony unfolds as brands repeatedly bid against each other at auctions to reach their own lost customers. This wasteful spiral of acquisition, reacquisition, and re-reacquisition can only be broken through true N=1 Personalisation—treating each customer as genuinely unique.”

This transformation from AAA to OOO is enabled by three breakthrough innovations:

  • NeoMails and AI Twins (collectively, NeoMartech) for building lasting relationships.
  • NEON (NeoAdtech’s foundation) for transforming how brands retarget, remarket, and reactivate existing (and identified) customers.

Together, these innovations address marketing’s fundamental challenges: creating reliable hotlines, enabling true personalisation, and eliminating wasteful reacquisition costs.

Thinks 1492

NYTimes reviews “Context Collapse”: “To [Ryan] Ruby, poetry is a “media technology” — a method for circulating content — currently undergoing “context collapse.” This recently coined term refers to the way that, on social media, you find yourself speaking to everyone everywhere — and thus to no one in particular, nowhere, in a context defined by a lack of common understanding.”

FT: “On a fundamental level, the move from articles of a few hundred words to 280 characters in the 2010s meant a shift from even the modest amount of detail and subtlety in the average news report to a world of oversimplified takes. Trade-offs and complexity don’t get a look in. This isn’t just about short formats. Instant feedback in the form of likes and share counts quickly taught people that the best-performing content is generally exaggerated and hostile rather than moderate and nuanced. The emerging media landscape became unfavourable to an educated centrist establishment, but a boon to populists and radicals.”

WSJ: “Instead of lithium, [a] nascent battery tech uses a sodium compound called soda ash, which can be produced using table salt. Unlike lithium, sodium is easily accessible everywhere. Even better for the U.S. is that China must synthesize soda ash from salt, while it is cheap and plentiful here. In fact, with 92% of the world’s reserves, you might even say that the U.S. is the Saudi Arabia of the stuff…Sodium-ion batteries have a number of advantages over lithium-ion battery tech, including being tougher and potentially safer. They also have one big disadvantage, thanks to unavoidable realities of the periodic table—they are bulkier and heavier. Proponents of this new kind of battery say their size and weight disadvantages hardly matter in many applications, such as large, stationary batteries for capturing energy when the sun shines and the wind blows, and feeding it back to the power grid when they don’t. And researchers say that eventually, they may be able to produce sodium-ion batteries which would be small and light enough to be used in electric vehicles.”

Bloomberg: “Programs designed to encourage loyalty have gradually morphed into complex financial ecosystems – especially in the US, where airlines collect billions of dollars in revenue per year from them…Two big changes to frequent flyer programs of the past have underpinned this transformation. First, airlines overhauled how points are awarded. Customers today earn rewards based on dollars spent rather than how far they fly. Some three-quarters of airline points issued by major US carriers now come from credit-card spending, meaning that every swipe at the grocery store can theoretically get you closer to a free trip. At the same time, actually getting on a plane often earns less than before. While the change has widened the consumer base, it’s frustrated many people who remember the old system. Next, airlines altered how points are redeemed. One by one, major carriers abandoned the awards charts that had helped loyalty members know how many points they needed to put that dream vacation within reach. Instead, airlines moved to a “dynamic” pricing model that varies the value of points flight-to-flight and even day-to-day, based on real-time demand and availability.”

Arnold Kling: “If I were a college president, I would require every freshman to participate in this sort of debate tournament. If I were in charge of Twitter (or X or whatever), I would require users to participate in this sort of debating activity as a prerequisite for being allowed to post. As you know, I believe that knowledge comes from social learning, from the give and take between different viewpoints. I emphasize the process of how argument is conducted. My most well-known book, The Three Languages of Politics, reflected on the observation that pundits do not engage in open-minded argument with the other side, but instead use demagoguery and straw-manning to try to close the minds of people on their own side.”

From AAA to OOO: The NeoMarketing Revolution (Part 2)

Neo

A few months ago, I came across the term “Neocloud” in an essay on SemiAnalysis. The description intrigued me: “An AI Neocloud is defined as a new breed of cloud compute provider focused on offering GPU compute rental. These pure play GPU clouds offer cutting edge performance and flexibility to their customers, but the economics powering them are still evolving just as the market is learning how their business models work… AI Neocloud Giants, unlike traditional hyperscalers, focus almost exclusively on GPU Cloud services.”

I was struck by the use of the word “neo” and the clear differentiation it conveyed. Since then, I’ve adopted “neo” in much of my writing—NeoMail, NeoESP, NeoMartech, NeoAdtech, NeoSaaS—to encapsulate fresh perspectives and transformative innovations. Over time, as I’ve continued thinking and writing, I realised I was piecing together a new framework for the future of marketing: NeoMarketing.

The word “neo” derives from the Greek prefix neos, meaning “new” or “young.” Historically, it has been used to signal a break from tradition while retaining a connection to the original concept. It implies a reimagining, reinvention, or modernisation, breathing fresh life into established ideas while acknowledging their roots.

In historical contexts, “neo” has often marked ideological shifts or transformative movements. Take, for instance, neoclassicism, which sought to revive and reinterpret the classical art and architecture of ancient Greece and Rome, aligning them with Enlightenment ideals. Neo-Gothic architecture in the 19th century revived medieval styles, blending them with modern techniques, as seen in landmarks like London’s Houses of Parliament. Neorealism in post-World War II Italy revolutionised cinema by focusing on the struggles of ordinary people, rejecting escapist storytelling. In politics, neoconservatism emerged in the mid-20th century, combining traditional conservative values with proactive foreign policy strategies. Similarly, neoliberalism redefined liberal economic thought in the 20th century, prioritising free markets, globalisation, and deregulation in response to the post-war welfare state model.

More recently, the prefix has gained traction in technology and finance. Neobanks, for example, represent a modern, digital-first approach to banking, challenging traditional institutions by offering innovative, mobile-friendly services.

This recurring use of “neo” underscores its power as a shorthand for transformation—a nod to the past while signalling progress and innovation. It captures the essence of breaking free from legacy constraints while maintaining continuity with foundational principles. In each case, “neo” marks not just change, but meaningful evolution—taking what works from established systems while boldly addressing their limitations.

Drawing from this lineage, I find “neo” an apt descriptor for the paradigm shifts occurring in marketing today. NeoMarketing seeks to redefine the field, moving beyond traditional acquisition models and outdated frameworks. It represents a fresh approach, focused on ownership, personalisation, and multi-monetisation, tailored for the challenges of the digital age. Like other “neo” movements before it, NeoMarketing acknowledges marketing’s fundamental principles while proposing radical solutions to its most pressing problems.

Thinks 1491

NYTimes: “Short books offer something to read when you want to surrender to a story for longer than an hour, but not for days and days. They are hefty enough to immerse yourself in and often short enough to finish before midnight, even with a distracted, 21st-century attention span. Even with a headline-weary mind…In a small book with each perfect word in its perfect place, feel your own sorrows fade as you surrender to the spell of a story.”

Lant Pritchett: “Economists have a long history of measuring the costs of barriers to trade that introduce distortions in prices. So I actually was trained as a PhD economist my main field was trade. So you can measure the costs of having a tariff or a ban on certain goods by the price differential. So in a paper I did with a couple of co-authors, we measured as best we could the price differential of what an equivalent productivity worker would earn in the United States versus their home country. And we found that the price differential of equal productivity labour was a factor of five. And I say a factor of five ‘coz usually as economists, we measure price distortions as per cent. So you have a tariff of 10 per cent or 25 per cent, whereas this is 400 per cent. So, the tax essentially on the consumer of labour in a rich country has a 400 per cent tax on it. So it’s five times more costly than if you were allowed access to a worker who would willingly come and do the same job.”

NYTimes: “When companies build A.I. systems, they go big first: They feed these systems enormous amounts of data. The more data companies feed into these systems, the more powerful they become. Just as a student learns more by reading more books, an A.I. system can improve its skills by analyzing ingesting larger pools of data. Chatbots like ChatGPT learn their skills by ingesting practically all the English language text on the internet. That requires larger and larger amounts of computing power from giant data centers. Inside those data centers are computers packed with thousands of specialized computer chips called graphics processing units, or GPUs, which can cost more than $30,000 apiece. The cost is pushed higher because the chips, data centers and electricity needed to do this digital work are in short supply. Sean Holzknecht, chief executive of Colovore, a data center operator whose facilities are adopting specialized chips used to build A.I., said this new kind of computing facility cost 10 to 20 times what a traditional data center does.”

Arnold Kling: “Who do we tend to trust? a. People who communicate in a way that we can understand. You cannot learn chemistry from a lecturer speaking in Mandarin, unless you understand that language. b. People with a reputation for knowing what they are talking about. c. People with whom you feel a bond. You trust someone who appears to care about you. You distrust someone who you believe is willing to mistreat you. These are not necessarily the people that we should trust.”

Sarah Bird: “I think generative AI is materially different and more exciting than other AI technology, in my opinion. The reason is that it has this amazing ability to meet people where they are. It speaks human language. It understands your jargon. It understands how you are expressing things. That gives it the potential to be the bridge to all other technologies or other complex systems. We can take someone who, for example, has never programmed before and actually allow them to control a computer system as if they were a programmer. Or you can take someone who, for example, is in a vulnerable situation and needs to navigate government bureaucracy, but doesn’t understand all the legal jargon — they can express their questions in their own language and they can get answers back in a way that they understand. I think the potential for lifting people up and empowering people is just enormous with this technology. It actually speaks in a way that is human and understands in a way that feels very human — [that] really ignites people’s imagination around the technology.”

From AAA to OOO: The NeoMarketing Revolution (Part 1)

Time for Transformation

Ask B2C/D2C CMOs about their top challenges, and three priorities emerge: increasing Average Order Value (AOV), driving purchase frequency, and boosting repeat orders. Their default solution? Pour more money into Big Adtech platforms and obsess over click-to-conversion funnels.

This dependency has deepened with each advancement in ad targeting. The promise is seductive: sophisticated algorithms and real-time bidding delivering the right message to the right audience at the perfect moment. Yet this increasing precision masks a troubling reality – brands have essentially become digital sharecroppers, renting access to their own customers through expensive auctions.

The cost? Staggering. Brands now routinely spend 50-80% of their marketing budgets on Google and Meta’s “walled gardens.” Most troubling, a significant portion of this spend goes toward reaching customers already in their databases. As competition intensifies, Customer Acquisition Costs (CAC) continue to soar while Customer Lifetime Value (LTV) struggles to keep pace. The result is an expensive cycle of continuous reacquisition that drains resources and erodes profitability.

This addiction to “acquire, acquire, acquire” via adtech’s algorithmic efficiency has created three critical problems:

  1. The “No Hotline” Crisis: Despite collecting customer emails and phone numbers, brands lack reliable ways to engage on demand. Emails go unopened, SMS gets ignored, push notifications get blocked, and WhatsApp proves too expensive.
  2. The “Not for Me” Challenge: Generic messaging and basic segmentation fail to resonate with customers who expect personalised experiences. Despite mountains of data, true personalisation remains elusive.
  3. The “No Alternative” Trap: Lacking viable alternatives to reach customers at scale, brands find themselves trapped in Big Adtech’s ecosystem, forced to pay premium prices through Google and Meta just to reach customers already in their databases. This dependency, combined with ever-rising Customer Acquisition Costs (CAC), creates an expensive reacquisition cycle that makes sustainable growth impossible. Despite owning customer contact information, brands see no choice but to keep feeding more resources into these walled gardens.

Consider the irony: despite having more ways than ever to reach customers – email, SMS, push notifications, WhatsApp, social media, and targeted ads – brands struggle to create meaningful, sustainable engagement. They’ve traded relationship depth for targeting precision, customer understanding for algorithmic efficiency. Most troublingly, in their quest to solve the engagement puzzle, marketers often end up feeding more resources into the very systems that created their dependency in the first place, reinforcing a cycle that benefits Big Adtech while dampening their own profitability.

The situation grows more urgent as privacy regulations tighten, third-party cookies disappear, and consumers show increasing fatigue with intrusive advertising. The need for change is clear: brands must shift from acquisition addiction to re-engineering retention, from rented relationships to owned connections, from mass messaging to N=1 (segment of one) personalisation.

Marketing needs more than optimisation—it needs reinvention. It requires a “neo” revolution: NeoMarketing, a breakthrough paradigm to solve the trifecta of modern marketing—maximising LTV, minimising CAC, and multi-monetising customers. At its core, NeoMarketing represents a transformative shift: moving from the outdated, AdWaste-infested cycle of AAA (acquire, acquire, acquire) to the Profipoly-enabling model of OOO (Only Once/Ones).

Thinks 1490

NYTimes: “One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general. Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity…Large language models generate sentences one word at a time based on their estimates of probability. Their designers can make the models more creative by having them choose not the most probable next word but, say, the fifth- or 10th-most probable next word. That’s called raising the temperature of the model. One hypothesis for why the models sometimes hallucinate is that their temperature is set too high.”

FT: “Once known as a producer of everything from washing machines to chips, Hitachi has slimmed down, with a primary focus on digitising infrastructure and power grids…From the outside, Hitachi still looks like a sprawling conglomerate spread across train infrastructure, power grids and factory automation. But investors are convinced it has successfully broken conglomerate silos, applying IT and data science to become something like a management consultant to utilities, manufacturers and railway operators.”

Arm CEO Rene Haas: “At our core, we are computer architecture. That’s what we do. We have great products. Our CPUs are wonderful, our GPUs are wonderful, but our products are nothing without software. The software is what makes our engine go. If you are defining a computer architecture and you’re building the future of computing, one of the things you need to be very mindful of is that link between hardware and software. You need to understand where the trade-offs are being made, where the optimizations are being made, and what are the ultimate benefits to consumers from a chip that has that type of integration. That is easier to do if you’re building something than if you’re licensing IP. This is from the standpoint where if you’re building something, you’re much closer to that interlock and you have a much better perspective in terms of the design trade-offs to make.”

Sajith Pai: “I have been looking for a term, an acronym or a phrase that describes these families who speak English predominantly at home. These constitute an influential demographic, or rather a psychographic, in India – affluent, urban, highly educated, usually in intercaste or inter-religious unions. I propose to call them Indo-Anglians. Unlike Anglo-Indians, the original English-speaking community in India, who were Christians, Indo-Anglians comprise all religions, though Hindus dominate. Indo-Anglians are also a highly urban lot; concentrated in the top 7 large cities of India (Mumbai, Delhi, Bangalore, Chennai, Pune, Hyderabad and Kolkata) with a smattering across the smaller towns in the hills and in Goa.”

WSJ: “The outsize success of America’s talented entrepreneurs doesn’t stem from their superior intelligence. It comes from working at companies such as Google and Microsoft, which mine the technological frontier and expose employees to valuable knowledge, insights and opportunities. Apple is worth more than the 30 largest German companies combined. Apple’s employees and its alumni use their knowledge and training to create more value than their counterparts in Europe. Unlike Europe, the enormous success of American entrepreneurs motivated an army of talented Americans to get valuable on-the-job training, work longer hours, take risks and succeed. A small amount of success bubbles up from a large pool of failure.”

Thinks 1489

Debashis Basu: “While India has wasted three decades in muddling along, even after the so-called economic liberalisation of 1991, under the Modi government, there is a faint element of economic nationalism in schemes such as production-linked incentives (PLI) and Make in India. But for these schemes to be effective, it has to use the playbook of export champions. The incentive has to be linked to export, not just import substitution or higher production. Initially it will be hard, which will automatically reveal what needs to be done to make each of the sectors export-competitive. In each of the four countries that have recorded extraordinary growth, the government worked with the manufacturers to help them import technology, arranged cheap finance, culled the weaker players, and relentlessly imposed export discipline. India should learn from this and adapt.”

FT: “[Brain-computer interface (BCI)] devices use a variety of methods to collect signals from the brain, which are then interpreted using artificial intelligence and used to control computers. Neuralink, whose electrodes have been implanted in two people, says its devices have been used to play video games and manipulate computer-aided design software. The first brain implants in humans date back two decades, but recent advances in the electronics used to collect and transmit brain signals, as well as the machine learning needed to analyse and make sense of the data, have raised hopes that the devices could soon be medically useful.”

Cass Sunstein: “Could AI predict the outcome of a coin flip? Could AI have predicted in (say) 2006 that Barack Hussein Obama would be elected president of the United States in 2008? Could AI have predicted in (say) 2014 that Donald Trump would be elected president of the United States in both 2016 and 2024? Could AI have predicted in (say) 2005 that Taylor Swift would become a worldwide sensation? The answer to all of these questions is “No.” AI could not have predicted those things (and no human being could have predicted those things, either). There are some prediction problems on which AI will not do well; the reason lies not in randomness, but in an absence of adequate data. There are disparate challenges here, but all of them are closely connected to the knowledge problem, and in particular to the unfathomably large number of factors that account for some kinds of outcomes and the critical importance of social interactions. In important respects, the Socialist Calculation Debate and the AI Calculation Debate are the same thing.”

Andy Kessler: “How do you debunk conspiracy theories? It’s hard. First, they must pass the smell test. Most don’t. Then ask if someone can hold a secret for that long. Don’t believe movies, podcasters or even politicians. Find some real science. Most important, figure out who benefits from spreading the story. The trick is not to let your emotions get the better of you. Question authority.”

WSJ reviews Tae Kim’s book on Nvidia: “Artificial intelligence without Nvidia is impossible to imagine. Its chips are the building blocks for the AI infrastructure being developed by both entrenched technology giants and well-funded newcomers. Its software, called Compute Unified Device Architecture, or CUDA, lets developers take full advantage of Nvidia’s hardware: It’s the paraffin you toss on the dry tinder of Nvidia’s ever more potent and multiplying GPUs (graphics processing units).”