Azeem Azhar’s Exponential View is your beacon into the exponents of technology, economics and society.

🔮 AI & climate change; blockchain and the internet; medicine meets AI; Alexa's growth, Apple's error; cheese, MOOCs, rotary phones++ #200

I received a huge dose of optimism this week when I was in Dublin

Exponential View

Azeem Azhar’s Weekly Wondermissive: Future, Tech & Society 

This issue has been supported by Hanover Communications  
Hanover prepares brands for the age of AI
Read their report on the reputational challenges that come with the AI revolution

Dept of podcasts 🎧

The Exponential View podcast is supported by Spotify.

The podcast resumes next week after a short break.

If you haven’t listened to the series, find it wherever you listen to your podcasts. And if you have, please help me spread the word by leaving a review or rating. It really helps!

Exponential View is available on: Spotify (recommended) | iTunes | StitcherSoundcloudOvercastBreaker

Dept of the near future

🔮 Gradually, then suddenly. Tim O'Reilly on the “small changes which accumulate, and suddenly the world is a different place”, including his insights on ubiquitous AI; the decline of the US; the future of food; genetic engineering, and more.

💯 Chris Dixon on how the blockchain could allow us to build internet services that encapsulate the original intention community-led ethos of the internet. It is an appealing theory: combining the bottom-up, non-hierarchical nature of open-source with a mathematically-rigorous implementation of computational trust. (Two EV subscribers, Kevin Werbach and Kenn Cukier, discuss the blockchain, its trust and governance mechanics. Also, McKinsey & Co on blockchain’s Occam problem: the finance industry is cooling on it as little of substance was being delivered. Azeem’s comment: seems like a problem of exuberance before product-market fit. There is a high likelihood as Werbach, Dixon & I argue that blockchain is going to be a powerful, foundational technology. But technologies need time to mature and evolve, and generally one wants to find where the smartest developers are and how practitioners are evolving applications on a core technology like this. And generally, don’t follow the big dollars, shiny PowerPoint & crisp suits.)

🌍 What AI will mean for climate change. It’s complicated, argues David Victor. On the one hand, oil and gas firms are well positioned to use new analytical techniques to increase efficiency and get those wells flowing. But there are also transformative ways AI could help: by helping us focus adaptation strategies; by democratising & evolving effective local responses more rapidly; by differentially helping poorer communities to respond to the ravages of climate change. (Azeem’s comment: As a general purpose technology, AI could also reduce the cost of basic goods, through optimisations and efficiencies, a change that should benefit the poor more than the rich. I also reckon we can be hopeful that applying AI in biology, biochemistry and core scientific domains could help with specific technical developments that might mitigate or help adapt to the impact of climate change. See also, the mounting challenges for the insurance industry in dealing with climate change. Urban flood damage alone is forecast to jump 20-fold to about $1 trillion a year by 2050.)

🍿 Ocasio-Cortez vs Trump. Kara Swisher on the new tempo of politics and why the US President may have met his match—at least on social media.

💸 Venture capital is on fire. Nearly $100bn of deals in 2018, the highest level since 1999, even though the total number of deals declined. This is because of more megadeals. Seed funding actually declined as well. (See also: more startups pass on venture capital "jet fuel", and new types of capital are starting to emerge. Gerry Neumann explains the maths of venture capital and why VCs need to take high risks, with limited room for medium risk investing. Azeem’s comment: There are many sources of capital, with different risk appetites and different expectations. Choose wisely! Don't fuel your jet with forecourt diesel. And don't put rocket fuel into your moped.)

Dept of internet business

C-r-a-z-y. There are more than 100m Alexa-enabled devices worldwide, including about 150 that are not made by Amazon. The device had a bumper Christmas shopping season. I remember reading forecasts for voice devices back in 2016 which headily suggested a global installed base of 5-6m by 2018. And here we are with more than 20 times more than that. Of course, Apple via Siri, Google through Google Assistant and even Microsoft's Cortana have much larger user base that Alexa. (Siri and Google Assistant approach or exceed a billion; Microsoft announced monthly 150m users for Cortana last summer.)

And with those numbers come more predictions that 2019 will be the year voice commerce takes off. My prediction: it won’t, if I am bullish in the long term for voice as an interface. I don't believe we have adequately solved the user experience or the core natural language understanding techniques to really delight. Amazon trumpeted several Alexa use cases that were growing in this blog post, but ultimately music, timers and smart home integrations seem to be the dominant apps. Is it enough?

📺 Netflix and chill no more. As the technology commoditises, more studios are yanking content from Netflix and preparing to launch their own streaming services.

🤔 Americans over 65 are seven times more likely to share fake news on Facebook than the 18 to 29-year-olds.

Amazon's Ring subsidiary allowed large numbers of contractors in Ukraine unimpeded access to customer videos.

Ofo, the over-expansive bike-sharing business is teetering on the brink. (It was rumoured to be burning $25m per month.)

Apple is United’s biggest corporate customer globally, spending $35m a year on flights to Shanghai from SF alone (50 daily business class seats).

Apple's new phone will have three rear cameras.

🔥 Ben Thompson on Apple's errors.

Dept of AI & data

Eric Topol’s comprehensive survey on the convergence of AI and human doctors on the path to high-performance medicine. Long, deeply footnoted, and worth reading over two cups of coffee.

Topol argues

almost every type of clinician [...] will be using AI technology, and in particular deep learning, in the future

He reviews applications in radiology, dermatology, ophthalmology, mental health, health systems, patient experience and more.

One useful framing is his analogy between self-driving cars and medical applications. Topol reckons a level three equivalence (conditional automation, reliant on human experts as backup) is the likely object for medical AI, and not human-free level five autonomous vehicle makers are striving for.

This is a healthy dose of sobriety for outlandish technical claims about “replacing doctors” rather than augmenting health systems and improving outcomes.

And he cautions:

The field is certainly high on promise and relatively low on data and proof. The risk of faulty algorithms is exponentially higher than that of a single doctor–patient interaction, yet the reward for reducing errors, inefficiencies, and cost is substantial. Accordingly, there cannot be exceptionalism for AI in medicine—it requires rigorous studies.

One key requirement for AI diagnostics will be explainability. Here is a profile of Been Kim, a Google researcher, working on building interpretability for famously indecipherable machine learning systems. Recommended read.

After raising $1.2bn last year, Sensetime, the world's most well-funded AI startup, is after another $2bn. One of its products is Viper which will “process and analyse over 100,000 simultaneous real-time streams from traffic cameras, ATMs, and more to automatically tag and keep track of individuals.”

🔒 The US Census Department intends to use differential privacy to manage the 2020 Census. This should allow the dataset to be shared without compromising individual user privacy.

Reconciling deep learning with symbolic artificial intelligence: a handy survey of approaches that bridge symbolic and sub-symbolic approaches to AI.

Short morsels to appear smart at dinner parties

🔮 Apple & innovation; the fractality of geopolitics; AI & brains; energy progress; graphene, meat, smart toilets++ #199

I'm going carbon neutral, are you?

Exponential View

Azeem Azhar’s Weekly Wondermissive: Future, Tech & Society 

Dept of podcasts 🎧

The Exponential View podcast is supported by Spotify.

My conversation with OpenAI's Policy Director, Jack Clark, was a real treat to end 2018 with. If you haven't listened to it yet, I highly recommend it.

Heard that one? Here are the most popular episodes of Season 2 so far:

  1. Kai-Fu Lee on China as the AI superpower (Spotify | iTunes | Soundcloud)

  2. Matthew Taylor on the future of work and democracy in the information age (Spotify | iTunes | Soundcloud)

  3. Michael Liebreich on renewable energy, climate change and technology (Spotify | iTunes | Soundcloud)

Subscribe to the Exponential View podcast wherever you get your favourite podcasts:
Spotify (recommended) | iTunes | Soundcloud | Stitcher | Breaker | Overcast

And if you’ve listened to them, please pop over to iTunes and give us a five-star rating. It really helps!

Dept of the near future

😬 Apple missed their numbers. It's been fifteen years since Apple last revised their earnings downwards. MG Siegler breaks down what this means: Apple needs to continue to pivot towards services, treading a path that, ironically, Microsoft has already taken. Services made $10.8bn in revenues in the last quarter. That said, as we've previously pointed out, Apple has other irons in the fire. The Apple Watch is a bigger business than iPad ever was. Apple has at least 70 autonomous vehicles on the roads and 2,700 core employees working on autonomous driving. Although it isn't clear where its AV project is headed. (Kara Swisher, one of the most respected tech journalists in the world, reckons this undershoot is a sign of a general stalemate in innovation. I take a slightly different view to Kara who explicitly highlights "Uber, Airbnb, Pinterest and, yes, Tinder" as the "last cool set of companies". Our framework for evaluating what is worthwhile innovation needs to change. There are now bigger, more meaningful opportunities to rebuild the infrastructure of the economy than the thin patina provided by UX-driven apps, such as blockchain, quantum computing, clean tech & health tech.)

🔥 “[We] don't want to be their real-world mistake”, Arizonans attack Waymo's self-driving cars. “They didn’t ask us if we wanted to be part of their beta test.” A fascinating policy conundrum. Innovations are better polished in real-world environments. That is what we learnt from lean startup disciplines over the past two decades. But equally, the nature of modern network technologies, both purely digital ones like social networks and physical interlopers like robotaxis, is that they meaningfully impact those who haven't opted in to the experiment. This isn't the technology of the 70s, like my old Binatone TV Master Mk IV, these are services with measurable spillovers onto non-participants and the communities in which they live.

⚡ "What began as a mapping of human meaning now defines human meaning, and has begun to control, rather than simply catalog or index, human thought." Technology historian George Dyson's beautiful essay on the ascent of analogue systems' uncontrollable reign. Short, gorgeous, read it twice. (Also, Stephen Cave argues for democratising the development of AI systems to avoid a Kafkaesque future.)

🏁 Not the end of history. We're seeing disjunctures at many fractal dimensions of systems right now. Here, a recent Rand Corporation assessment of the emerging era of international competition describes: "global patterns of competition are likely to be complex and diverse, with distinct types of competition prevailing in different issue areas" involving "a drawn-out combination of contestation, competition, and cooperation in which "winning" or "victory" is the wrong mental model." Also check out some recent network science research suggests that war might be a phenomenon that emerges from the network structure of society, baked into the very web of relationships that connect us. This insight could also give us clues on how to avoid it. (See also, An Xiao Mina, we face a "death of consensus" not the death of truth. Authenticity and affiliation may matter more.)

Dept of AI

What does 2019 hold for AI: approaches requiring less training data; a focus on tackling operationalising AI; and increased conversations on the social and ethical considerations of building AI systems. Opinions from Hilary Mason, Andrew Ng, Rumman Chowdhury & Yann LeCun.

Some fascinating breakthroughs in the space of AI and health:


🇫🇮 How Finland is educating its population about AI.

The machine learning race really is a data race: how firms need to find differentiated data.

Using algorithms to nudge workers towards happiness.

Algo-trading is a useful system to explore the broad interactions amongst autonomous systems. One result is herd-like trading behaviour.

Dept of energy transition

Electric vehicle adoption has blown away most forecasters, OPEC and Bloomberg New Energy Finance alike. (Our view has been more closely aligned with Tony Seba, we think the transition can happen faster than most forecasters have predicted because of the multiple exponential improvements across battery, drive train, distribution & marketing.)

🌟 Tesla had a stunning year. The firm delivered 91,200 vehicles in the fourth quarter of 2018, a four-fold increase compared to the same period two years earlier. It is now the top luxury car seller in the US. Elon Musk may be eccentric, laddish & hubristic but the leadership Tesla shows in making electric vehicles quotidian deserves acknowledgement. (Check out this mind-boggling video of Model X owners at a meetup in Changsha, Hunan, China.)

🛴 The coming explosion in light electric vehicles.

2018 was a good year as US coal product slumped to its lowest for nearly 40 years. See also: renewables overtake coal as Germany's main source of energy.

Good news from the UK, too: electricity generation fell to the lowest point since 1994, while renewables rise to 33% of total power generated in 2018.

🌡️ Stark visualisation of temperatures in the UK from 1772 to 2018.

Short morsels to appear smart at dinner parties

🥩 Alternative proteins: Switching from beef to alternative proteins would have significant health and emissions benefits (perhaps as much as 2% of all global emissions), according to new research from WEF and Oxford Martin School. (Note: I've only had time to digest the executive summary and not the full report.)

Plant-based food that mimics meat has been part of the Chinese cuisine for hundreds of years, having originated in Buddhist monasteries. Now it's finding the market in the West.

Censoring China's Internet for stability and profit. A detailed investigation into the private sector firms which monitor China's internet. Super interesting.

🇮🇳 The Chinese takeover of the Indian app ecosystem. "The message is clear for the Chinese — if you want growth, conquer India."

🧐 Fascinating data on dApp (blockchain distributed app) adoption in 2018.

🚻 The Internet-connected toilet. #privacy

Porn sites collect more data than traditional streaming services. And it shows. #privacy

😂 Mobile payments + arm wrestling: true innovation in China (video)

The 'magic angle' that gives graphene previously unexpected properties.

🧬 'Omnigenic' model suggests that all genes influence our complex traits and diseases.

🚀Human colonisation will be the first global change on Mars since the atmospheric loss a billion year ago, and other ways humans will impact the Red Planet.

End note

🔮🌟 The top stories of 2018; reviewing my predictions; what to look forward to in 2019++ #198

What I got wrong about 2018 was fascinating.

Exponential View

Azeem Azhar’s Weekly Wondermissive: Future, Tech & Society 

We’re at the mercy of your inbox filters, and they’ve been quite harsh following our transition from Mailchimp to Substack, a newsletter delivery platform. If you find this issue in your spam, please do the following:

  1. drag the email from your spam to inbox,

  2. add my email to your contacts,

  3. mark the email as important or star it.


Dept of podcasts 🎧

The Exponential View podcast is supported by Spotify.

Hundreds of years ago you had a community of monks who had been stewarding civilization through the dark ages and had been keeping knowledge alive. They had access to privileged information, privileged knowledge, and privileged institutions. Then the printing press came along, and messed everything up for them. I think that the AI research community is going through this period now, where they're figuring out which of them are monks, which of them are peasants, which of them should be doing printing presses, and which of them should be keeping information private.

In the last episode of the Exponential View podcast in 2018, I discuss the state of artificial intelligence, the geopolitics of technology, and Edison’s elephant with Jack Clark, the Policy Director at OpenAI.

Subscribe to the Exponential View podcast and get the latest episode:
Spotify (recommended) | iTunes | Soundcloud | Stitcher | Overcast | Breaker

Reviewing my 2018 predictions 🔎 

At the end of last year, I published some predictions which were pulled together with the help of many readers. How did we fare?

Broadly speaking, we did very well. The strain on the international political economy, caused by the Second Great Divergence, as technological capabilities accelerate away from existing social systems, exacerbated. Facebook’s altercations with many governments being an exemplar. But we’ve also seen India’s government take steps against global e-commerce players. I predicted that Silicon Valley would hire outside fixers to solve these problems, or at least, improve their optics. Britain’s Europhile politician, Nick Clegg, starts a new job at Facebook in the new year. And we’re increasingly seeing the spotlight shine on Amazon and its control of commerce on its platform.

We also, roughly speaking, got the trend of innovation and scaling outside of Silicon Valley right. Chinese companies continued to scale very fast. Some like, Toutiao, delivered novel experiences that became the envy of the best in the West. Deep tech firms effloresced in areas like post-von Neumann compute, computational chemistry and other fields. Many outside of the Valley.

Our AI themes: more money, increased corporate prioritisation, focus towards human augmentation, progress in fair and transparent AI, and others were well represented this year. AI is booming, as I discuss with Jack Clark in the latest podcast (above). Equally, our calls on autonomous vehicles, cyber attacks, augmented reality, venture investment in health-tech and ad-tech fracas played out well.

What I got wrong was fascinating.

I thought that crypto technologies would start to show their utility this year. But it seems that true utility is still a few quarters away. I was ambivalent about whether the speculative bubble would pop, and thought money would probably continue to flow into crypto assets as institutions prepared to introduce new crypto products. In fact the speculative bubble popped, and fraud almost rivalled greed in its prevalence. The result was a retrenchment by traditional institutions from these spicy products.

The most well-funded crypto firms (even in the enterprise space) started to retrench and cut costs. The absence of evidence of real use cases was replaced by an evidence of absence of real use cases. Next year will likely be more productive for blockchain, as the dust clears.

I also underestimated the rottenness of Facebook. I’ve long drawn attention to the problems created by Facebook’s monoculture, its denial of an editorial role, its lackadaisical attitude towards the pollution caused by its attention model, or its role in debasing the public space. But I simply didn’t understand quite how deep this would run, and how it would spread across so many aspects of its business.

Facebook’s turpitude is legion: occluding honest debate and investigation via legions of mealy-mouthed communications; regularly faking its metrics (for its advertisers); its imperial powers of censorship and control, swung by the political axe of the public policy team; its comical belief that it made real progress in addressing its structural failings.

The firm continued to disgrace itself, having almost fully reversed its Midas Touch, in ways I didn't predict.

I also wrongly predicted increased Russian disinformation during the 2018 US mid-terms. Some argue that the Russians largely sat out those 2018 elections. What we did see was more evidence of disinformation and computational propaganda in many other geographies, promulgated by a wide host of actors.

In short, I think we, with the help of many readers, did reasonably well in reckoning on 2018.

I’ll endeavour to put some predictions together for 2019 for next week’s issue.

In the meanwhile, the rather brilliant Isaac Asimov put forward some predictions for 2019 back in 1984. They are worth reading.

Top 10 most popular stories of 2018 💯

10: Michael Osborne’s presentation on automation at work.

9: Michael Liebreich on pro-growth environmentalism.

8: How Microsoft is succeeding despite the end of Windows.

7: 2018 as predicted by people in 1918.

6: How data science and interactive notebooks may represent the future of the scientific paper.

5: How to predict a technology’s commercial success.

4: Human history in one chart.

3: Silicon Valley’s soul-sucking machine.

2: The Apple Watch is a bridge to the future.

1: Ark Invest’s Big Ideas for 2018.

End note

It felt like 2018 was a really dark year.

A dark year for politics, as populists continued to win elections around the world with divisive manifestos built on walls and scapegoats rather than bridges and inclusion. For those of us in Britain, the fact-light & insalubrious Brexit debate is an object lesson.

It was a dark year for the technology industry, whose behemoths are still trying to get to grip with their new systemic role in the world. Microsoft and Apple, two of the oldest, are doing a better job than the whippersnappers, like Amazon and Facebook. Big Tech feels more like a Gordon Gecko cigar, than Steve Jobs’ bicycle for the mind.

But equally, with only two business cycles left to get us to a net zero carbon emissions world, I find it profoundly depressing to see so much time, attention and talent being poured into firms like Epic Games, which makes Fornite, and Juul, an epidemically successful peddler of nicotine. Our future is not going to be assured by doing the Floss while huffing a Juul vape.

As I have learnt a little about early-stage investing with my friends at Kindred Capital, I have delighted in seeing more entrepreneurs wanting to tackle more meaningful problems: like female health, non-meat proteins, improved software tooling for AI, or tackling sustainability questions. And the amazing progress we've seen in the broad field of AI from research shops like OpenAI and DeepMind gives us cause for optimism. More so is the speed with which the insights of expensively-discovered avenues of exploration can move into more widely-available open source techniques, for all to use (Read this wonderful New Yorker essay on AlphaGo and LeelaZero.)

And equally, I’m starting to see some interesting intellectual commonalities emerge, especially around the tricky question of how we create economies which can halt the carbon-crisis while ensuring well-being. In my discussions with Kate Raworth (a sustainability economist who is roughly-speaking left-leaning) and Michael Liebreich (a climate change expert on the right), I saw more in common between them than I saw apart. A slew of economists and policy people, such as Bill Janeway, Mariana Mazzucato, Diane Coyle, Matthew Taylor and others, are reinvigorating the importance of the state in guiding innovation for social rather than individual purposes. (Many of these conversations are available on the podcast series. If you haven't tried podcasts, I recommend you do.)

And so, there remain reasons to be, in Paul Romer's words, "conditionally optimistic". (This year had many isolated bright spots as these fifteen charts show.)

Conditional optimism is not believing that if the market signals it or the customer demands it, then it must be right. Conditional optimism is not the bare naked solutionism of a lean startup powered by venture capital and a cheering demo day.

Conditional optimism is not "not complacent optimism. Instead of suggesting that we can relax because policy choices don’t matter, it suggests to the contrary that policy choices are even more important than traditional theory suggests."

2019 will be another challenging, difficult year. It is always darkest before dawn. But dawn will, ultimately, break.

Happy New Year!


P.S. Saying Happy New Year via this tweet or LinkedIn post would be most appreciated! 🥂

🔮 The new authoritarianism; technological innovation; automating the middle class; Chinese clickfarms, meditation wars, Martian ice++ #197

Eroom's Law strikes again

Exponential View

Azeem Azhar’s Weekly Wondermissive: Future, Tech & Society

This issue has been supported by Hanover Communications  
Hanover prepares brands for the age of AI
Read their report on the reputational challenges that come with the AI revolution

We’re at the mercy of your inbox filters, and they’ve been quite harsh following our transition from Mailchimp to Substack, a newsletter delivery platform. If you find this issue in your spam, please do the following:

  1. drag the email from your spam to inbox,

  2. add my email to your contacts,

  3. mark the email as important or star it.


Dept of podcasts 🎧

The Exponential View podcast is supported by Spotify.

We need to build a new kind of networked solidarity, as we are in this unprecedented moment of fine grain data about ourselves. The old kinds of ways of building connections and relationships are falling away, and we haven't quite yet as a society figured out what's going to replace that. But we know, from Durkheim, something has to, otherwise societies don't function very well.

I'm in conversation with Gina Neff, Senior Research Fellow and Associate Professor at the Oxford Internet Institute and at the Department of Sociology, University of Oxford. Gina and I explore the intricacies of self-tracking in a data-abundant economy; we roam the space between sociology and technology as we discuss the value of sociological perspective in tech product development.

Subscribe to the Exponential View podcast and get the latest episode:
Spotify (recommended) | iTunes | Soundcloud | Stitcher | Overcast | Breaker

Dept of the near future

🔎 “Social media's ability to simultaneously solicit and surveil communication has not only turned the dream of individuali[s]ed, expressive democracy into a fountain of wealth. It has turned it into the foundation of a new kind of authoritarianism” argues Fred Turner in this must-read essay. The "political vision that created social media in the first place... distrusts public ownership and the political process while celebrating engineering as an alternative form of governance." (See also, the Indian government broadened legislation allowing it to intercept and monitor citizen's computers.)

🥟 China has probably become the world’s biggest economy and will reap the benefits that once flowed to the U.S. Excellent perspective from Noah Smith.

✨ A gorgeous long read by Jerry Neumann: Technological innovation, the iTunes case study.

🤦 Facebook facepalm. More details on Facebook's approach to user data, which tells us some new details but also shines more light on a rotten culture. A number of firms are touting the idea of people selling their data—an approach I think cannot be the only approach to tackling personal data on the net. One journalist tried: and secured 0.3 cents for his. Facebook's WhatsApp has a nasty, unchecked and growing paedophilia problem. At the same time, Facebook is building a cryptocurrency team to facilitate person-to-person payments on WhatsApp.

💨 "A couple of decades ago, it was perfectly normal to smoke cigarettes inside... today, very few would do that. I think it’s the same with cars in the city [centre]." Oslo joins many cities banning cars from the centre.

🤖 How to prepare the middle class for automation: Even in the most positive scenarios for automation and the labour force, there will be a difficult adjustment period in which entire classes of people will struggle to find their place in the new economy. How should we tackle it?

Dept of artificial intelligence

How computers got shockingly good at recognising images. An accessible guide to the milestone breakthroughs in 2011/2 which kicked off the current deep learning wave.

💯 Tim Dettmers’ straightforward guide to hardware for deep learning.

📉 Eroom's Law strikes again: Richard Jones argues that Eroom's Law, the observation that R&D productivity in pharma has been falling exponentially, has also struck the semiconductor industry.

Geoff Hinton, one of the lead architects of deep learning, suggested explainability was unimportant in AI systems. Several researchers disagreed.

An overview of the London AI ecosystem.

Short morsels to appear smart at dinner parties

Amazing video of China's click-fraud farms.

💸 A basic income experiment in Germany to launch in 2019.

🌌 NASA’s captivating guide through the life and death of planetary systems.

Pendulum dance. Stunning

How the attempt to turn Silicon Valley into a manufacturing hub for Apple failed.

🧘 The battle of meditation apps.

⛸️ A picture of the 50-mile wide Korolev ice crater on Mars.

End note

As I mentioned last week, I've started my Christmas break so this week is part of the holiday schedule. I also had a really complex house move which naturally led to a few days of total media blackout. The result is a much shorter penultimate Exponential View for 2018.

We have one more cracking issue coming out next week on December 30th.

Next Wednesday, we also have the last episode of the Exponential View podcast of 2018. This is an insanely awesome conversation on the state of artificial intelligence with Jack Clark, the director of policy at OpenAI, and facilitator of the rather brilliant AIIndex. If you haven't yet got into podcasts, give this one a try as well.

If you get some time off around Christmas in your part of the world, have a great break.

See you next week,

P.S. Exponential View readers are up to some amazing stuff. Scroll down!

What you are up to

Congrats to Igor Carron whose optical-chip startup, LightOn, raised $3m to accelerate machine learning performance.

Congrats to the number of EV readers involved in Graphcore which just closed a Series D funding round valuing the ML chip firm at $1.7bn.

Anab Jain and Superflux built a highly experiential simulation of the future of work.

Self-driving pioneer, Antony Lewnadowski, claims to have driven coast-to-coast using his own autonomous vehicle. EV reader, Mark Harris, reports. It is controversial, another EV reader, Alex Roy, an expert on autonomous vehicles himself, is sceptical.

We've heard from nearly 300 of you joining our directory of experts. If you haven't added yourself, please take a moment.

🔮 The Bill of Data Rights; AI progress; the purpose of the corporation; geo-anthropology; Chinese chips, asexual rice & naughty seals++ #196

The internet is being pulled in four different directions

Exponential View

Azeem Azhar’s Weekly Wondermissive: Future, Tech & Society

This issue has been supported by Hanover Communications  
Hanover prepares brands for the age of AI
Read their report on the reputational challenges that come with the AI revolution

🎧 Dept of podcasts

At the current rate that we are emitting we'll use up our carbon budget by 2030. We've got twelve years. It’s just two business cycles away. If you think about 2030, where you have to have either reduced emissions by a quarter to a half or you're in a situation where there's no carbon budget: your social license to emit at that point will be gone. And that is going to be the environment that you finish your career in.

The founder of New Energy Finance (now Bloomberg New Energy Finance) and the leading expert on clean energy, transportation, and climate finance, Michael Liebreich, joins me in this latest episode of the Exponential View podcast. We discuss our climate reality, the pathways to the necessary energy transition, and technologies to get us there.

Subscribe to the Exponential View podcast and listen here:

iTunes | Spotify | Stitcher | SoundCloud | Breaker | Overcast

Dept of the near future

💥 The Bill of Data Rights: Must read by Martin Tisné, a long-time friend of this newsletter. We need a new “paradigm [which captures] the ways in which an ambient blanket of data changes our relationships with one another—as family, as friends, as co-workers, as consumers, and as citizens. To do so, this paradigm must be grounded in a foundational understanding that people have data rights and that governments must safeguard those rights.” See also this eye-popping New York Times investigation: Your apps know where you were last night, and they are not keeping it a secret: “Dozens of companies use smartphone locations to help advertisers and even hedge funds. They say it’s anonymous, but the data shows how personal it is.”

🌍 “Letters and numbers are an almost weightless media, but they provide a means to organize states, move legions and run economies [...] The impact of information technologies on societies and physical environments is thus not limited to modern times [...] As meatspace and cyberspace converge today, what we cannot lose sight of is Earthspace. We are obliged to treat the ‘critical zone’, the thin but highly complex layer of life extending from the lower atmosphere to the upper lithosphere, with duty and care.” Impressive essay from the Max Planck Institute on the need for a new interdiscipline, Geo-anthropology, to take an integrative perspective of the interplay between digital and natural domains. (Weirdly this was a sponsored article in Nature, and the first time I think I've ever recommended a post like this in 196 issues. It is worth a read, nonetheless.)

💯 The 2018 edition of the AI Index highlights further acceleration in the performance of AI systems, research in AI, a boom in demand for relevant skills and continued investment. The whole document is highly accessible and worth reading. It shows a dramatic increase in activity across the board. I'll highlight one technical performance milestone: the training of ImageNet, a popular image recognition network, has dropped from 60 minutes to just 4 minutes in about 18 months. (Nick Statt's overview of the report is decent.)

🇨🇳 The internet is being pulled in four different directions by Washington, Beijing, Brussels and Silicon Valley, argues Wendy Hall. Thought-provoking insight into what can be thought of as a reflection of our newly multipolar world. (See also, how Chinese fintechs are looking to capture the mobile payments markets in India, Asia and Africa, as those populations come online. This could shift the global balance of power in the finance industry as those huge populations become connected and wealthier. And this detailed overview of the Chinese intention to develop their own semiconductor industry, specifically chips for ML workloads, and break dependence on US firms.)

🤤 Fascinating: food company Mondelez suffered $100m in damages as a result of a NotPetya cyberattack. Their insurers, Zurich, are refusing to paying citing an exclusion on the basis that NotPetya was a ‘hostile or warlike’ action by a government. (See also, The EU Security Commissioner claimed that the Kremlin ran a year-long disinformation campaign prior to seizing Ukrainian ships last week. And a US cybersecurity firm also suggested that two Russian hacker entities were also involved in attacks around the time of the Kerch Strait incident, which may highlight the hybrid nature of modern power projection. And this on how Chinese hackers seem to be running amok confidential US Navy systems.)

🎩 It is time to rethink the purpose of the corporation, argues Martin Wolf. Long-time bugbear of mine is the naive Milton Friedman view that corporations should solely focus on profits for shareholders, and the equally naive view that corporations should just provide what the “customer wants”. (See also, Salesforce hires a Chief Ethical and Humane Use Offer. The question is whether that person is put in an appendix like so many CSR folk, or actually sits across an organisation changing the actual output of the firm and goals pursued.)

🔥 The UN report on climate change may have understated the pace. The unfortunate syzygy of carbon emissions, air pollution & climate cycles, will be driving faster change resulting in the 1.5 °C warming level arriving a decade earlier. (See also, London is implementing a climate change and disaster risk reduction plan.)

Dept of experts

I am building a small directory of experts who are also EV readers. It is just a way for me to understand better who I can turn to if I need to understand a particular area better. We'll keep this directory private, but if you'd like to be included, please add your name to the form here. Two hundred and fifty-one of you already have.

It'll help when I'm looking for expert commentary, interviews, podcasts, etc. Please fill this out even if you know me really well. I don't want to overlook your expertise because of our familiarity!

To add yourself to the (private) directory, click here.

Particularly interested in any of the key EV domains, including genetics, AI (research, implementation, policy), renewables, drones, crypto assets & blockchain, cultural trends, business models, geopolitics, cybersecurity. Front-line expertise, as well as macro expertise, is welcome. Written a book on the subject? Or backed an entrepreneur in a relevant field? All welcome.

Dept of technology smorgasbord

🤖 The robots descend on Trump country: “The growing use of work robots and the deployment of artificial intelligence have been most disruptive in just those areas of the country that provided President Trump with crucial margins of support in 2016” argues Thomas Edsall.

🌐 Excellent critique by a developer, Julien Genestoux: “The end of the ad-supported Web. What if we got the business model of the web wrong?

Vice documentary on Chinese social credit in action.

Training neural nets while maintaining the privacy of data.

📈 Forrester Research: The rise of edge computing.

Generative adversarial networks are now so good at creating realistic images that these faces are indistinguishable from real people.

Short morsels to appear smart at dinner parties

Loading more posts…