Insights on today's (horizon 1) and tomorrow's (horizon 2, 3) evolution and adoption of distributed, scalable, resilient and intelligent data analytics, cloud services and infrastructure

Cloud + Edge Horizons

If network effects are one of the most important concepts for software-based businesses, then that may be especially true of data network effects -- a network effect that results from data. Particularly given the prevalence of machine learning and deep learning in startups today.

But simply having a huge corpus of data does not a network effect make! So how can startups ensure they don't get a lot of data exhaust but get insight out of and add value to that data and the network? How can they make sure that the (arguably inevitable) data aspect of their business isn't just a sideshow or accident? How should founders strike the balance between not overbuilding/ building a data team vs. having enough data for those data scientists to work with in the first place? And finally, what are the ethical considerations of all this?

The a16z general partners most focused on bio and fintech -- Vijay Pande and Alex Rampell -- join this episode of the a16z Podcast to share their observations and advice on all things data network effects.

a16z Podcast: Data Network Effects

In this episode of Conversations in the Cloud Bart Schachter, COO of Iron.io and Travis Reeder, CTO and Co-founder of Iron.io, discuss making job processing faster and easier. Iron.io has been using Docker containers for a number of years with the core purpose of helping companies run workloads. Companies leverage Iron.io to deploy those workloads fast, process files/data faster, iterate quicker, and gain workload control. Iron.io is making the transition to function as a service: the transition from bigger monolithic apps to micro-service, and now breaking down micro-services into smaller chunks of code. They foresee the industry moving to a multi-cloud and hybrid environment, which is why the workloads that they manage have been intelligently routed to multiple clouds. Iron.io will leverage SNAP to understand the landscape of the data center and to better land workers on hardware that provides advantageous instruction sets. To find out more go to www.iron.io or follow Iron.io on Twitter at https://twitter.com/getiron.

Iron.io Predicts a Multi-Cloud, Hybrid Environment - CitC Episode 66

Wesley Reisz talks to Sid Anand, a data architect at cybersecurity company Agari, about building cloud-native data pipelines. The focus of their discussion is around a solution Agari uses that is built from Amazon Kinesis Streams, serverless functions, and auto scaling groups.

Sid Anand is an architect at Agari, and a former technical architect at eBay, Netflix, and LinkedIn.  He has 15 years of data infrastructure experience at scale, is a PMC for Apache Airflow, and is also a program committee chair for QCon San Francisco and QCon London.

Why listen to this podcast

 - Real-time data pipeline processing is very latency sensitive
 - Micro-batching allows much smaller amounts of data to be processed
 - Use the appropriate data store (or stores) to support the use of the dataIngesting data quickly into a clean database with minimal indexes can be fast
 - Communicate using a messaging system that supports schema evolution

More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2rJU9nB

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Show Notes

Sid Anand on Building Agari’s Cloud-native Data Pipelines with AWS Kinesis and Serverless

In this episode of the O’Reilly Programming Podcast, I talk with Matt Stine, global CTO of architecture at Pivotal. He is the presenter of the O’Reilly live online training course "Cloud-Native Architecture Patterns," and he has spoken about cloud-native architecture at the recent O’Reilly Software Architecture Conference and O’Reilly Security Conference.

Matt Stine on Cloud-Native Architecture

When you have “a really hot, frothy space” like AI, even the most basic questions — like what is it good for, how do you make sure your data is in shape, and so on — aren’t answered. This is just as true for the companies eager to adopt the technology and get into the space, as it is for those building companies around that space, observes Joe Spisak, Head of Partnerships at Amazon Web Services. “People treat it like magic,” adds a16z general partner Martin Casado.

This magical realism is especially true of AI, because by definition — i.e., machines learning — there is a bit of a “black box” between what you put in and what you get out of it. Which may be fine… Except when you have to completely change the data being fed into that black box, or you’re shooting for a completely different target to come out of it. That’s why, observes Scott Clark, CEO and co-founder of SigOpt, “an untuned, sophisticated system will underperform a tuned simple system” almost every time.

So what does this mean for organizations going from so-called “toy” problems in R&D to real business results tied to KPIs and ROI? In this episode of the a16z Podcast, Casado, Clark, and Spisak (in conversation with Sonal Chokshi) share their thoughts on what’s happening and what’s needed for AI in practice, given their vantage points working with both large companies and AI startups. What does it mean for data scientists and domain experts? For differentiation and advantage? Because even though we finally have widely available building blocks for AI, we need the scaffolding too… and only then can we build something powerful on top of it.

a16z Podcast: AI, from 'Toy' Problems to Practical Application

In 2017 The Economist declared data to be the world's most valuable resource. And yet “data insight” is one of those phrases that, while important, is now so ubiquitous it’s been numbed of meaning. So how do you actually get the most meaningful insights from your data, and what does that look like as you also think about crafting the best customer experience? When and what is the best way to use this information... without getting to the dystopian future depicted in, for instance, Minority Report?

This episode of the a16z Podcast (based on a discussion that took place at a16z's annual summit event in November 2017) features Suhail Doshi, co-founder and CEO of Mixpanel; Gil Elbaz, founder and CEO of Factual; and Jeff Glueck, CEO of Foursquare; moderated by Lauren Berson. It covers everything from using data to understand context and one's customer base to what personalization really means and how data can impact the physical world.

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The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.
 
This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

a16z Podcast: Data, Insight, and the Customer Experience

Sit down with us this week to hear the Executive Director of the Cloud Native Computing Foundation talk about how CNCF got started, which projects are its fastest growing (besides Kubernetes), what the Foundation has to offer as far as training and certification, what you'll find on their interactive landscape, and what their Serverless Working Group is up to.

Ep38: Dan Kohn on the Cloud Native Computing Foundation

In this episode of the O’Reilly Media Podcast, I talk with JP Phillips, platform engineer at IBM Cloud. IBM is driving development in the container space, as shown through last year’s launch of Istio, an open cloud service that allows developers to connect, manage, and secure networks of different microservices. Istio, a joint collaboration between IBM, Google, and Lyft, (in conjunction with the Cloud Native Computing Foundation), is platform agnostic and runs on Kubernetes platforms, such as IBM’s Cloud Container Service. Interest in the platform is growing. IBM's Daniel Berg, who is giving a talk on Istio at the upcoming OSCON conference in Portland, recently led a hands-on workshop at KubeCon in Copenhagen to help developers learn how Istio can solve common challenges with microservices deployed within Kubernetes.

Kubernetes and Containers for Enterprise Developers

“The rules of the game are different in tech,” argues — and has long argued, despite his views not being accepted at first — W. Brian Arthur, technologist-turned-economist who first truly described the phenomenon of “positive feedbacks” in the economy or “increasing returns” (vs. diminishing returns) in the new world of business… a.k.a. network effects. A longtime observer of Silicon Valley and the tech industry, he’s seen how a few early entrepreneurs first got it, fewer investors embrace it, entire companies be built around it, and still yet others miss it… even today.

If an inferior product/technology/way of doing things can sometimes “lock in” the market, does that make network effects more about luck, or strategy? It’s not really locked in though, since over and over again the next big thing comes along. So what does that mean for companies and industries that want to make the new technology shift? And where does competitive advantage even come from when everyone has access to the same building blocks (open source, APIs, etc.) of innovation? Because Arthur — former Stanford professor, visiting researcher at PARC, and external professor at Santa Fe Institute who is also known as one of the fathers of complexity theory in economics — has written about the nature of technology and how it evolves, observing that new technology doesn’t come out of nowhere, but instead, is the result of “combinatorial” innovation. Does this then mean there’s no such thing as a dramatic breakthrough?!

In this hour-long episode of the a16z Podcast, we (Sonal Chokshi with Marc Andreessen) explore many of these questions with Arthur. His answers take us from “the halls of production” to the “casino of technology”; from the “prehistory” to the history of tech; from the invisible underground autonomy economy to the “internet of conversations”; from externally available information to externalized intelligence; and finally, from Silicon Valley to Singapore to China to India and back to Silicon Valley again. Who’s going to win; what are the chances of winning? We don’t know, because it’s a very different game… Do you still want to play?

a16z Podcast: Network Effects, Origin Stories, and the Evolution of Tech

This episode of the Data Show marks our 100th episode. This podcast stemmed out of video interviews conducted at O’Reilly’s 2014 Foo Camp. We had a collection of friends who were key members of the data science and big data communities on hand and we decided to record short conversations with them. We originally conceived of using those initial conversations to be the basis of a regular series of video interviews. The logistics of studio interviews proved too complicated, but those Foo Camp conversations got us thinking about starting a podcast, and the Data Show was born.

To mark this milestone, my colleague Paco Nathan, co-chair of Jupytercon, turned the tables on me and asked me questions about previous Data Show episodes. In particular, we examined the evolution of key topics covered in this podcast: data science and machine learning, data engineering and architecture, AI, and the impact of each of these areas on businesses and companies. I’m proud of how this show has reached so many people across the world, and I’m looking forward to sharing more conversations in the future.

The Evolution of Data Science, Data Engineering, and AI

In this episode of the Data Show, I spoke with Ashok Srivastava, senior vice president and chief data officer at Intuit. He has a strong science and engineering background, combined with years of applying machine learning and data science in industry. Prior to joining Intuit, he led the teams responsible for data and artificial intelligence products at Verizon. I wanted his perspective on a range of issues, including the role of the chief data officer, ethics in machine learning, and the emergence of AI technologies for enterprise products and applications.

The Real Value of Data Requires a Holistic View of the End- to-End Data Pipeline

There are over 20 million programmers out there -- and double that, if you count everyone else coding in other ways -- but where are the next 100 million developers? How do we get to a billion developers? The answer, observes a16z general partner Peter Levine in conversation with GitHub co-founder and former CEO Chris Wanstrath (based on a Q&A recorded at our last a16z Summit event) lies in changing the very definition of a "programmer" and "programming".

It might even mean the end of code, argues Levine (who apparently loves arguing the end of things!), and the beginning of a future where data isn't just "the new oil", but one where we all become our own "oil wells". With everyone is manipulating data -- the new programming, in a sense -- expertise can be scaled (especially with new tools) so everyone gets the answers and solutions they need. So what does this mean for open source developers? CIOs and organizations that have lots of different data streams, as well as domain experts? This episode of the a16z Podcast covers all this and more, including touching briefly on what's ahead...

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The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.
 
This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

a16z Podcast: The End (and Beginning) of Programming

Joining us this week is Simon Crosby, CTO at SWIM.AI. Simon discusses the architecture for Edge and its differences from existing cloud infrastructure and how the SWIM.AI solution meets the needs for Edge services.   

 Highlights
•	Challenges in Edge 
•	Data is Complete Disruption in Current Models 
•	Don’t Train in Cloud for Edge; Instead Learn on Fly
•	All About Data – Apps can’t be Written for Data Specifically 
•	Example of Sensor Model at Traffic Light in Self-Learning Model
•	Digital Twin Concept & Actor Model 
•	SWIM.AI Innovation ~ always as though its local 
•	Independent Management of Latency and Resource Utilization 
•	Write the Program from the Data
•	Example of Manufacturer with Millions of RFID Tags 
•	Limitations of Having People Involved in Everything

Simon Crosby on Revolutionary Architecture Requirements for Edge

In a recent episode of the O’Reilly Media Podcast, we spoke with George Miranda about the importance of service mesh technology in creating reliable distributed systems. As discussed in the new report The Service Mesh: Resilient Service-to-Service Communication for Cloud Applications, service mesh technology has emerged as a popular tool for companies looking to build cloud-native applications that are reliable and secure.

During the podcast, we discussed the problems a service mesh infrastructure solves and the service mesh features you’ll find most valuable. We also talked about how to choose the right service mesh for your organization, the challenges involved in getting it deployed to production, and the best ways for getting started with a service mesh.

How to Choose and Deploy a Service Mesh

Joining us this week is Yves Boudreau from Ericsson for his 2nd Podcast appearance (1st Podcast).  

 Highlights
•	Edge as an accelerant not having to wait until Edge is built completely 
•	Opportunity Cost using Edge as is; no time to wait
•	Be Specific when Requesting Services
•	Internet and Networks are Not Unlimited Pipes
•	Interesting Use Cases for Edge – Augmented Reality, Drone, Cars, Batteries 
o	Jason Hoffman Podcast for Batteries 
•	Cost savings of where the data processing is done
•	Open Source software communities at the Edge

Yves Boudreau on State of the Edge Report and Edge vs Cloud

with Chris Dixon (@cdixon), Ali Yahya (@ali01), and Devon Zuegel (@devonzuegel)

“Show me the incentive and I'll show you the outcomes.”

At the end of the day, observes a16z crypto general partner Chris Dixon, Satoshi's whitepaper [the original bitcoin paper outlining a peer-to-peer decentralized network and blockchain sans centralized third parties] is nine pages of incentives. It's the kind of incentive design that you can use to build many other things on the internet (which itself is driven by very simple core protocols and could even upgrade itself as a result). But only with the right incentives (and alignment of those incentives among different entities), of course. Which is where cryptonetworks come in -- especially since they don't rely on hardware buildout (as with earlier generations of internet deployment), but rather on software (which is essentially just logic, the kind of building block you can use to build countless other things). The breadth of possibilities is endless.

This means that platforms and networks (and operating systems, for that matter) can spend less time, energy, money, and frankly, suffering due to fighting -- thanks to distorted business models that lead them to extract value from users and compete among complements (vs. substitutes/better alternatives). The internet-native business models baked into crypto, however, could lead to greater competition and better options for users.

But what are the missing building blocks, that can help make such networks more iterated games vs. one-off prisoner's dilemmas? And what will it take for these networks to truly reach web-scale, as it's still just the beginning? Because decentralization is the means to an end -- not the end in and itself -- observes a16z crypto partner Ali Yahya, so what do we need to build next to get there? In this episode of the a16z Podcast (guest hosted by freelance software engineer and writer Devon Zuegel), Dixon and Yahya share their thoughts on where we've been, and where we're going with the internet.



Please note that the a16z crypto fund is a separate legal entity managed by CNK Capital Management, L.L.C. (“CNK”), a registered investor advisor with the Securities and Exchange Commission. a16z crypto is legally independent and operationally separate from the Andreessen Horowitz family of fund and AH Capital Management, L.L.C. (“AHCM”). 

In any case, the content provided here is for informational purposes only, and does NOT constitute an offer or solicitation to purchase any investment solution or a recommendation to buy or sell a security; nor it is to be taken as legal, business, investment, or tax advice. In fact, none of the information in this or other content on a16zcrypto.com should be relied on in any manner as advice. You should consult your own advisers as to legal, business, tax and other related matters concerning any investment.

Furthermore, the content is not directed to any investor or potential investor, and may not be used or relied upon in evaluating the merits of any investment and must not be taken as a basis for any investment decision. No investment in any fund advised by CNK or AHCM may be made prior to receipt of definitive offering documentation and due diligence materials. Finally, views expressed are those of the individual a16z crypto personnel quoted therein and are not the views of CNK, AHCM, or their respective affiliates. 

Please see https://a16zcrypto.com/disclosures/ and https://a16zcrypto.com/disclaimers/ for further information.

a16z Podcast: Cryptonetworks and Decentralization -- Building Blocks

with Andrew Chen (@andrewchen), Jeff Jordan (@jeff_jordan), and Sonal Chokshi (@smc90)

Growth is one of the most top of mind questions for entrepreneurs building startups of all kinds (and especially consumer ones) -- but how does one go beyond a mindset of "growth hacking" to thinking about growth more systemically and holistically? What are the key metrics to know; why; and how?

This episode of the a16z Podcast -- one of two in a series -- focuses on the user acquisition aspect of growth, followed by engagement and retention in the next episode. Featuring a16z general partners Andrew Chen and Jeff Jordan, in conversation with Sonal Chokshi, the discussion also covers the nuances of paid vs. organic marketing (and the perils of blended CAC); the role of network effects; where does customer lifetime value (LTV) come in; and much more. Because at the end of the day, businesses don't grow themselves...

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The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.
 
This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

a16z Podcast: The Basics of Growth 1 -- User Acquisition

with Devon Zuegel (@devonzuegel), Denis Nazarov (@iiterature), and Jesse Walden (@jessewldn)

The open source movement enabled so much in computing, including the collaborative building of libraries -- that is, building blocks of code that developers could combine together to build applications. But as these applications grew to massive scale, those libraries ended up being somewhat asymmetrical for "nights-and-weekend" developers (compared to say, the disproportionate resources of a large company with billions of users and big data).

Blockchains, however -- enabled by cryptotokens that align incentives among stakeholders -- shift open source development from libraries, to the creation of shared, open, permissionless services. Instead of being siloed and repetitively produced as if from the industrial factory era, any smart contract developed on Ethereum becomes a shared service that can interact with any other service... incentivizing developers to improve on existing services, build on top of them, and enable combinatorial innovation at greater scale than ever before.

But if decentralized networks are to win the third era of the internet, how will we resolve challenges such as single-purpose services (another form of consolidation), community conflicts, and other issues? In this video, freelance software engineer (and blockchain app developer) and writer (and urban watcher) Devon Zuegel guest-interviews a16z crypto partners Denis Nazarov and Jesse Walden, the co-founders of Mediachain Labs (which was acquired by Spotify in 2017). They draw on their past experiences leading open source development of a decentralized media attribution protocol for connecting creators to their audience, and what the implications of "services vs. libraries" could be for creatives now. And what about identity, stablecoins and crypto finance, and more? Finally, they extend their previous analogy of cities and network effects and how it fits the idea of libraries vs. services in crypto.

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Please note that the a16z crypto fund is a separate legal entity managed by CNK Capital Management, L.L.C. (“CNK”), a registered investor advisor with the Securities and Exchange Commission. a16z crypto is legally independent and operationally separate from the Andreessen Horowitz family of fund and AH Capital Management, L.L.C. (“AHCM”). 

In any case, the content provided here is for informational purposes only, and does NOT constitute an offer or solicitation to purchase any investment solution or a recommendation to buy or sell a security; nor it is to be taken as legal, business, investment, or tax advice. In fact, none of the information in this or other content on a16zcrypto.com should be relied on in any manner as advice. You should consult your own advisers as to legal, business, tax and other related matters concerning any investment.

Furthermore, the content is not directed to any investor or potential investor, and may not be used or relied upon in evaluating the merits of any investment and must not be taken as a basis for any investment decision. No investment in any fund advised by CNK or AHCM may be made prior to receipt of definitive offering documentation and due diligence materials. Finally, views expressed are those of the individual a16z crypto personnel quoted therein and are not the views of CNK, AHCM, or their respective affiliates. 

Please see https://a16zcrypto.com/disclosures/ and https://a16zcrypto.com/disclaimers for further information.

a16z Podcast: Crypto and the Evolution of Open Source

Speaker(s): Professor Adam Tooze | In September 2008 the Great Financial Crisis, triggered by the collapse of Lehman brothers, shook the world. A decade later its spectre still haunts us. As the appalling scope and scale of the crash was revealed, the financial institutions that had symbolised the West's triumph since the end of the Cold War, seemed - through greed, malice and incompetence - to be about to bring the entire system to its knees. In this talk Adam Tooze will talk about his new book, Crashed: How a Decade of Financial Crises Changed the World. Crashed is an analysis of what happened and how we were rescued from something even worse - but at a price which continues to undermine democracy across Europe and the United States. Gnawing away at our institutions are the many billions of dollars which were conjured up to prevent complete collapse. Over and over again, the end of the crisis has been announced, but it continues to hound us - whether in Greece or Ukraine, whether through Brexit or Trump. Adam Tooze (@adam_tooze) is the author of The Deluge and The Wages of Destruction.The Wages of Destruction won the Wolfson Prize for History and the Longman-History Today Book of the Year Prize. He has taught at Cambridge and Yale and is now Kathryn and Shelby Cullom Davis Professor of History at Columbia University. He is an alumnus of the London School of Economics and Political Science. Tim Frost is a Chair of credit asset manager Cairn Capital and a Trustee of Step Change the debt charity. He served in the British Army in Germany and the Falkland Islands and ran a hostel for homeless people before spending 15 years at JP Morgan, where he helped to establish the credit derivatives business. Tim is an Emeritus Governor and alumnus of the London School of Economics and Political Science, and was appointed a Director of the Bank of England in 2012.

Crashed: how a decade of financial crises changed the world [Audio]

with Steven Johnson (@stevenbjohnson), Chris Dixon (@cdixon), and Sonal Chokshi (@smc90)

There's a lot of research and writing out there on "thinking fast" -- the short-term, gut, instinctual decisions we make, biases we have, and heuristics we use -- but what about for "thinking slow" -- the long-term decisions we make that both take longer to deliberate and have longer spans of impact on our lives... and the world? Because we're not only talking about decisions like who to marry (or whether to move) here; we're also talking about decisions that impact future generations in ways we as a species never considered (or could consider) before.

But... why bother, if these decisions are so complex, with competing value systems, countless interacting variables, and unforeseeable second- and third-order effects? We can't predict the future, so why try? Well, while there's no crystal ball that allows you to see clearly into the future, we can certainly try to ensure better outcomes than merely flipping a coin, argues author Steven B. Johnson in his new book, Farsighted: How We Make the Decisions That Matter Most.

Especially because the hardest choices are the most consequential, he observes, yet we know so little about how to get them right. So in this episode of the a16z Podcast, Johnson shares with a16z crypto general partner Chris Dixon and a16z's Sonal Chokshi specific strategies -- beyond good old-fashioned pro/con lists and post-mortems -- for modeling the deliberative tactics of expert decision-makers (and not just oil-company scenario planners, but also storytellers). The decisions we're talking about here aren't just about individual lives and businesses -- whether launching a new product feature or deciding where to innovate next -- they're also about even bigger and bolder things like how to fix the internet, or what message to send aliens with outcomes spanning centuries far into the future. But that's where the power of story comes in again.


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The content provided here is for informational purposes only, and does not constitute an offer or solicitation to purchase any investment solution or a recommendation to buy or sell a security; nor it is to be taken as legal, business, investment, or tax advice. In fact, none of the information in this or other content on a16zcrypto.com should be relied on in any manner as advice. Please see https://a16zcrypto.com/disclosures/ for further information.

Cloud + Edge Horizons

brucemacv