The document discusses several areas where technological development has lagged despite potential, including:
1. Aerospace and transportation - Space travel remains prohibitively expensive and transportation technologies have not improved radically in 30 years.
2. Biotechnology - Progress in increasing lifespans and drug development has slowed despite DNA discovery and computing advances. Lack of data, high capital costs, and slow discovery processes hinder the field.
3. Advanced machines/software - While computer hardware rapidly improves, software advances more slowly. We lack powerful analytical tools and true artificial intelligence despite decades of predictions. Robotics remains niche.
The document argues investing in technologies that reduce costs in these areas could both generate high returns and vastly increase
Inbae Lee - A Quick Look at the Korean Startup SceneInbae Lee
This is my presentation I used at a VC networking event in Korea, in an attempt to give outsiders a general understanding on what the Korean startup ecosystem consists of at the moment, on a very rudimentary level. Hope you enjoy.
한국 스타트업 현황을 외국인이 이해하기 쉽게 간단히 정리해 본 슬라이드입니다.
(note: some of the figures might be confusing due to having been polled from various research or media sources.)
* This presentation was chosen as the top presentation in 2014 by SlideShare team
I had a chance to make a speech in an international conference and touched the startup basics and a little bit of Korean startup locations. This has many slides but you can read it in 5 mins :)
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
Are We In a Bubble? #Wayra #CorpAccel #AcceleratedStartupVitaly Golomb
Keynote at Corporate Accelerator 3.0 / Wayra conference
London June 15th, 2017 - Vitaly M. Golomb
What are and are not startups?
3rd Industrial Revolution
Global Ecosystems
Technology Lifecycle S-Curve
Innovation Clusters
Corporate Venture Capital
Artificial Intelligence
Augmented Reality
Automotive Revolution
AI for Fintech
Digital Health
Investment Trends
Blended Reality
Hyper Mobility
Internet of All Things
Smart Machines
3D Transformation
Inbae Lee - A Quick Look at the Korean Startup SceneInbae Lee
This is my presentation I used at a VC networking event in Korea, in an attempt to give outsiders a general understanding on what the Korean startup ecosystem consists of at the moment, on a very rudimentary level. Hope you enjoy.
한국 스타트업 현황을 외국인이 이해하기 쉽게 간단히 정리해 본 슬라이드입니다.
(note: some of the figures might be confusing due to having been polled from various research or media sources.)
* This presentation was chosen as the top presentation in 2014 by SlideShare team
I had a chance to make a speech in an international conference and touched the startup basics and a little bit of Korean startup locations. This has many slides but you can read it in 5 mins :)
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
Are We In a Bubble? #Wayra #CorpAccel #AcceleratedStartupVitaly Golomb
Keynote at Corporate Accelerator 3.0 / Wayra conference
London June 15th, 2017 - Vitaly M. Golomb
What are and are not startups?
3rd Industrial Revolution
Global Ecosystems
Technology Lifecycle S-Curve
Innovation Clusters
Corporate Venture Capital
Artificial Intelligence
Augmented Reality
Automotive Revolution
AI for Fintech
Digital Health
Investment Trends
Blended Reality
Hyper Mobility
Internet of All Things
Smart Machines
3D Transformation
This is made from this schedule (https://riseconf.com/schedule) to make clear the parallel sessions.
There is no guarantee that this is up-to-date. If you find any mistake, please point me out.
At any given moment it is easy to look back to see how technology has changed over time. At the same time it is difficult to see what transformations are taking place in current moment, and even more difficult to see where things are going.
We will explore what technology is. For us it may be the latest tech stuff we see, something new. But what about everyday objects that we take for granted. Are those not technologies also?
How does technology evolve and where did it come from? We look at some ideas on evolution of technology and how it is similar to biology in some ways. We will also look at the origin of the word technology. Finally we will define the term we will use in the course. Terms defined are technology, product performance, and innovation to name few.
Red Giant Syndrome - How to turn around a tech juggernaut on the verge of imp...Jump Associates
We all know huge tech companies suffering from Red Giant Syndrome: Yahoo!, Research In Motion, AOL, Nokia. Companies, once dominant in their markets, that continue to sell a huge number of products and services yet are losing consumers and customers at an alarming rate. Barring radical change, each is bound to collapse within a few years.
We call this situation Red Giant Syndrome. The term, borrowed from astronomy, originally refers to when a star exhausts the supply of hydrogen that has sustained it for millions of years and begins gobble up any bits of matter it can convert into fuel to sustain its existence. Consequently, they grow to hundreds of times their original volume while dramatically dropping in density. Over time, this imbalance leads to collapse.
But it doesn't have to be that way. IBM and Apple - both once "Red Giants" - successfully came back from the verge of implosion. How did they do it? We explain the 3 critical steps in this Slideshare. To read the accompanying article, head over to Forbes. http://blogs.forbes.com/jump/
Design by: Laura Polkus, http://www.laurapolkus.com
Presentation by Tuomo Alasoini, Chief Adviser, Tekes (the Finnish Funding Agency for Innovation). The presentation consists of remarks based literature and presentations at the BRIE-ETLA & SWiPE seminar. The seminar was held on 30 August 2016 in the Business and Work in the Era of Digital Platforms research seminar in Helsinki, Finland, where SWiPE, Smart Work in the Platform Economy research project was launched. The seminar was hosted jointly by BRIE-ETLA and SWiPE research projects.
The social life of ideas: From innovation to profitHay Group India
The main challenge in organizational innovation lies in its execution, and not in having more ideas. Top companies create supportive cultures that transform ideas into profitable investments.
Companies need innovation to survive. In fact, there is no shortage of clever people and smart ideas. Hence the competitive edge comes from having the best execution – from the time the idea is first identified, shepherded through the corporate maze, and into the hands of the paying customer.
And yet, in many companies, the chase for short-term profitability can become the Achilles heel of long-term business sustainability. The way to avoid this is to have a deep-rooted culture that promotes innovation and new ideas to filter up and sideways.
The Guide to the New York Startup Scene is a resource for startups, investors, entrepreneurs or anyone interested in seeing what the Big Apple has to offer the growing tech scene.
This is made from this schedule (https://riseconf.com/schedule) to make clear the parallel sessions.
There is no guarantee that this is up-to-date. If you find any mistake, please point me out.
At any given moment it is easy to look back to see how technology has changed over time. At the same time it is difficult to see what transformations are taking place in current moment, and even more difficult to see where things are going.
We will explore what technology is. For us it may be the latest tech stuff we see, something new. But what about everyday objects that we take for granted. Are those not technologies also?
How does technology evolve and where did it come from? We look at some ideas on evolution of technology and how it is similar to biology in some ways. We will also look at the origin of the word technology. Finally we will define the term we will use in the course. Terms defined are technology, product performance, and innovation to name few.
Red Giant Syndrome - How to turn around a tech juggernaut on the verge of imp...Jump Associates
We all know huge tech companies suffering from Red Giant Syndrome: Yahoo!, Research In Motion, AOL, Nokia. Companies, once dominant in their markets, that continue to sell a huge number of products and services yet are losing consumers and customers at an alarming rate. Barring radical change, each is bound to collapse within a few years.
We call this situation Red Giant Syndrome. The term, borrowed from astronomy, originally refers to when a star exhausts the supply of hydrogen that has sustained it for millions of years and begins gobble up any bits of matter it can convert into fuel to sustain its existence. Consequently, they grow to hundreds of times their original volume while dramatically dropping in density. Over time, this imbalance leads to collapse.
But it doesn't have to be that way. IBM and Apple - both once "Red Giants" - successfully came back from the verge of implosion. How did they do it? We explain the 3 critical steps in this Slideshare. To read the accompanying article, head over to Forbes. http://blogs.forbes.com/jump/
Design by: Laura Polkus, http://www.laurapolkus.com
Presentation by Tuomo Alasoini, Chief Adviser, Tekes (the Finnish Funding Agency for Innovation). The presentation consists of remarks based literature and presentations at the BRIE-ETLA & SWiPE seminar. The seminar was held on 30 August 2016 in the Business and Work in the Era of Digital Platforms research seminar in Helsinki, Finland, where SWiPE, Smart Work in the Platform Economy research project was launched. The seminar was hosted jointly by BRIE-ETLA and SWiPE research projects.
The social life of ideas: From innovation to profitHay Group India
The main challenge in organizational innovation lies in its execution, and not in having more ideas. Top companies create supportive cultures that transform ideas into profitable investments.
Companies need innovation to survive. In fact, there is no shortage of clever people and smart ideas. Hence the competitive edge comes from having the best execution – from the time the idea is first identified, shepherded through the corporate maze, and into the hands of the paying customer.
And yet, in many companies, the chase for short-term profitability can become the Achilles heel of long-term business sustainability. The way to avoid this is to have a deep-rooted culture that promotes innovation and new ideas to filter up and sideways.
The Guide to the New York Startup Scene is a resource for startups, investors, entrepreneurs or anyone interested in seeing what the Big Apple has to offer the growing tech scene.
Learning's from book: The steve jobs way:
Key Aspects covered: Thoughts of steve jobs on:
Marketing
Team
Competition
Product and Design
Organization
Be your self
1. Методика проведення рольового тренінгу дидактичного характеру
2. Рольовий тренінг дидактичного характеру - це форма організації навчальної діяльності. Мета : виховання в учасників тренінгу ставлення до себе як до діяча.
3. Показниками розвитку у вчителя ставлення до себе як до діяча є такі вміння:
4. Організація рольового тренінгу в системі післядипломної педагогічної освіти :
5. Методи розгортання рольового тренінгу
Every passing year advances are getting bigger and bigger and happening more and more quickly. It suggests some pretty intense things about our future. In the twenty-first century, billion-dollar industries can be disrupted and waylaid virtually overnight—no sector of commerce or government is immune to the threat.
Clipperton - AI - Deep Learning: From Hype to Maturity?Stephane Valorge
Paris, London, Berlin – September 2017 - Clipperton, a leading European corporate finance boutique focused on the High Tech and Media industries announces the release of a Research Paper covering the recent trends and evolution in the Artificial Intelligence industry, with a particular focus on the hottest topic of the last 18 months: Deep Learning.
DIGITAL LEADERSHIP: An interview with Saul Klein Partner with Index VenturesCapgemini
Saul Klein, Partner with Index Ventures
Saul Klein is a Partner with Index Ventures, one of the largest venture capital firms specializing in technology investments. Saul has 20 years of experience in building tech companies in both the US and Europe. He is the co-founder of Kano and Seedcamp; he also co-founded and was the original CEO of Lovefilm International, which was acquired by Amazon; and part of the original executive team at Skype, which was acquired by eBay. Capgemini Consulting spoke to Saul Klein to examine the disruptive impacts of startups and their implications for traditional incumbents.
The following document was elaborated by InPeople Consulting & UpsideRisks as a consecuence of the participation at the Conference Exponential Finance and their own research.
Scenarios for Smart Devices in 2025: Brave New Smartphone and/or Black Mirror?3G4G
Presented by David Wood, Principal, Delta Wisdom
In this talk anticipating future scenarios for smart devices, futurist and smartphone industry pioneer David Wood suggests answers to a number of key questions. What are the key trends we should be watching, to see if they'll ever emerge from a slow disappointing phase into a fast and furious phase? How might these trends combine to shake up present-day usage patterns? Will the successors of the smartphone accelerate a Brave New World, and/or make Black Mirror a reality? And what can we learn from past predictions of future smartphone scenarios?
*** Shared with Permission ***
Summary of the Book Exponential organizationsGMR Group
Happy Morning
I have made a small attempt to summarize this book after reading this number of times.
In this book Salim Ismail gives a deep dive – Exponential Organizations where he shows how any company, from Startup to a multi-national , can become exponential.
The author unveils years of research learning how organizations can accelerate growth through use of Technology. The goal of the book is to provide you with the knowledge to leverage assets such as big data, communities, algorithms, and new technology to achieve performance ten times better than your competition.
It is good book for entrepreneurs who need a guide for harnessing and strategizing the hyper growth of a company that feeds off of modern technology in the 21st century and beyond.
Because we focus on accelerating technologies and the future we identified an infection point in how we build businesses that has never noticed before.
Most CEOs see innovation as product or service innovation. But there is also process innovation, social innovation, organizational innovation, management innovation, business model innovation etc.
Those business that do not evolve , will not survive
Happy Reading
One of the great irony of successful companies is how easily they can fail. New companies are founded to take advantage of some new technology. They become highly successful and but when the technology shifts, something new comes along, they are unable to adapt and fail. This is the innovator’s dilemma.
Then there are companies that manage to survive. For example, Kodak survived two platform shift, only til fail the third. IBM has survived over 100 years. What do successful companies do differently?
Inspiration is fine, but above all, innovation is really a managem.docxjaggernaoma
Inspiration is fine, but above all, innovation is really a management process
Ask most people who invented the lightbulb, and they will promptly provide the wrong answer: Thomas Alva Edison. Truth is, the famous inventor's 1879 debut of his incandescent light trailed others by decades. So why does he get all the glory? Mostly because of what he did next, notes Andrew Hargadon, author of How Breakthroughs Happen: The Surprising Truth about How Companies Innovate. To get his creation to the masses, Edison and his team of engineers in Menlo Park, N.J., spent years building the entire electric system, from light sockets and safety fuses to generating facilities and the wiring network. Only then did the electric light flare into the innovation that lit the world.
In short, Edison beat all his predecessors at one crucial task: managing the whole process of innovation, from light-bulb moment to final product. Today that task is scarcely easier than it was 125 years ago. Sure, it's easy to get lucky once in a while. The real trick is doing it over and over again. "Managing innovation means cultivating an environment where lightning can strike twice," says Paul Saffo, research director at the think tank Institute for the Future. "It's extraordinarily difficult."
To hard-headed business people, innovation often seems as predictable as a rainbow and as manageable as a butterfly. Penicillin, Teflon, Post-it Notes -- they sprang from such accidents as moldy Petri dishes, a failed coolant, and a mediocre glue. It's no wonder so many executives throw up their hands. "Our approach has always been very simple, which is to try not to manage innovation," shrugs Silicon Valley venture capitalist Michael Moritz, a partner with Sequoia Capital. "We prefer to just let the market manage it."
Yet even in the Darwinian chaos of Silicon Valley, innovations are made, not born. The world's most innovative companies, from Procter & Gamble and Toyota Motor to Apple Computer and Edison's own General Electric, make their own luck. They plunge ahead on new ideas even though they know most will fail. "You have to go down blind alleys," says Jeffrey P. Bezos, founder and chief executive of pioneer online retailer Amazon.com Inc. "But every once in a while you go down an alley and it opens up into this huge, broad avenue. That makes all the blind alleys worthwhile."
"COMMODITY HELL"
Problem is, a lot of forces today conspire against innovative products getting to market. Small outfits that are often the most innovative get short shrift because buyers aren't sure they can deliver or even survive to keep supporting their products. And for large corporations, there's the "innovator's dilemma" coined by Harvard Business School professor Clayton Christensen. By catering to their best customers with increasingly advanced and more expensive products -- a seemingly sensible approach -- successful companies ignore or even discourage less profitable low-end products. But as startups.
Eric Jackson's presentation to Yahoo outlining his plan to slash the company’s workforce by 75%, replace Marissa Mayer with an operations-focused CEO and bring in a strategic partner to help navigate the tax issues surrounding its Asian assets.
Source: http://www.wsj.com/public/resources/documents/yahoopresentation.pdf
The internal report from The Times's new ideas task force headed by Arthur Gregg Sulzberger. (Missing pages: 9, 11, 19, 21, 22)
Originally published by BuzzFeed: http://www.scribd.com/doc/224332847/NYT-Innovation-Report-2014
More: www.buzzfeed.com/mylestanzer/exclusive-times-internal-report-painted-dire-digital-picture
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
1. F OUND E RS F UND
WHAT HAPPENED TO THE FUTURE?
IN T R O D UC T IO N
We invest in smart people solving difficult problems, often difficult scientific or engineering problems. Here’s why:
The Problem
We have two primary and related interests:
01. Finding ways to support technological development (technology is the fundamental driver of growth in the industrialized world).
02 . Earning outstanding returns for our investors. 1
From the 1960s through the 1990s, venture capital was an excellent way to pursue these twin interests. From 1999 through the present, the
industry has posted negative mean and median returns, with only a handful of funds having done very well. What happened?
VC’s Long Nightmare
To understand why VC has done so poorly, it helps to approach the future through the lens of VC portfolios during the industry’s heyday,
comparing past portfolios to portfolios as they exist today. In the 1960s, venture closely associated with the emerging semiconductor
industry (Intel, e.g., was one of the first – and is still one of the greatest – VC investments). In the 1970s, computer hardware and software
companies received funding; the 1980s brought the first waves of biotech, mobility, and networking companies; and the 1990s added
the Internet in its various guises. Although success now makes these investments seem blandly sensible, even obvious, the industries
and companies backed by venture were actually extraordinarily ambitious for their eras. Although all seemed at least possible, there
was no guarantee that any of these technologies could be developed successfully or turned into highly profitable businesses. When H-P
developed the pocket calculator in 1967, even H-P itself had serious doubts about the product’s commercial viability and only intervention
by the founders saved the calculator. Later, when the heads of major computing corporations (IBM, DEC) openly questioned whether
any individual would ever want or need a computer – or even that computers themselves would be smaller than a VW – investment in
companies like Microsoft and Apple in the mid-1970s seemed fairly bold. In 1976, when Genentech launched, the field of recombinant DNA
technology was less than five years old and no established player expected that insulin or human growth hormone could be cloned or
commercially manufactured, much less by a start-up. But VCs backed all these enterprises, in the hope of profiting from a wildly more
advanced future. And in exchange for that hope of profit, VC took genuine risks on technological development.
In the late 1990s, venture portfolios began to reflect a different sort of future. Some firms still supported transformational technologies
(e.g., search, mobility), but venture investing shifted away from funding transformational companies and toward companies that solved
incremental problems or even fake problems (e.g., having Kozmo.com messenger Kit-Kats to the office). This model worked for a brief
period, thanks to an enormous stock market bubble. Indeed, it was even economically rational for VCs to fund these ultimately worthless
companies because they produced extraordinary returns – in fact, the best returns in the industry’s history. And there have been
subsequent bubbles – acquisition bubbles, the secondary market, etc. – which have continued to generate excellent returns for VCs lucky
enough to tap into them. But these bubbles are narrower and the general market more demanding, so VCs who continue the practices of
the late 1990s (a surprising number) tend to produce very weak returns. Along the way, VC has ceased to be the funder of the future, and
instead has become a funder of features, widgets, irrelevances. In large part, it also ceased making money, as the bottom half of venture
produced flat to negative return for the past decade. 2
1. We have somewhat greater incentives than many other firms to figure out the answers to these questions as the partners and employees of Founders Fund are collectively
the largest investors in our funds (by contrast, industry convention only requires VCs to put up 1% of the total capital of the fund – the perhaps misleadingly named GP
“commitment”). At FF, about 20% of the total capital we manage is our own capital.
2. E.g., https://www.cambridgeassociates.com/pdf/Venture%20Capital%20Index.pdf
2. We believe that the shift away from backing transformational technologies and toward more cynical, incrementalist investments broke
venture capital. Excusing venture’s nightmare decade as a product of adverse economic conditions ignores the industry’s long history
of strong, acyclical returns for its first forty years, as well as the consistently strong performance of the top 20% of the industry. What
venture backed changed and that is why returns changed as well.
Not Everything With A Plug Is Technology
Not all technology is created equal: there is a difference between Pong and the Concorde or, less glibly, between Intel and Pets.com.
Microprocessing represents real technological development, peddling pet food on-line, less so. Conversely, things that may be dismissed
as fake technologies (Amazon and Facebook occasionally receive this critique) often resolve very challenging technological problems.
Among its many innovations, Amazon helped develop intelligent customer recommendations and logistical efficiencies that allow
you to order almost anything, anytime, and get it the next day; Facebook developed ways to manage large numbers of connections
in a computationally efficient way, create an effective developer ecosystem, and to make it pleasurable to administer your on-line
relationships. These also deserve attention, of course: though the Internet is no longer the virgin field it once was, we dismiss as bunk the
idea that the Internet is tapped out. Web companies that fail are the companies that fail to exploit the true power of the medium. 3
Over time, the market tends to call out fake technologies and companies, which makes it a risky proposition to invest in them – it’s
possible to flip a born loser and make a handsome return, but you need to get lucky with timing (i.e., sell into a bubble). 4 Real technology
companies tend to create durable returns, making timing much less important. If you invested in webvan.com, your window of
opportunity was measured in months; if you backed Intel, your window of opportunity was measured in decades. Therefore, as investors,
we should seek companies developing real technologies.
Are There Any Real Technologies Left?
Have we reached the end of the line, a sort of technological end of history? Once every last retailer migrates onto the Internet, will that be
it? Is the developed world really developed, full stop? Again, it may be helpful to revisit previous conceptions of the future to see if there
are any areas where VC might yet profitably invest.
In 1958, Ford introduced the Nucleon, an atom-powered, El Camino-shaped concept car. From the perspective of the present, the Nucleon
seems audacious to the point of idiocy, but consider at the time Nautilus, the first atomic submarine, had just been launched in 1954 (and
that less than ten years after the first atomic bomb). The Nucleon was ambitious – and a marketing gimmick, to be sure – but it was not
entirely out of the realm of reason. Ten years later, in 1968, Arthur C. Clarke predicted imminent commercial space travel and genuine (if
erratic) artificial intelligences. “2001: A Space Odyssey” was fiction, of course, but again, its future didn’t seem implausible at the time; the
Apollo program was ready to put Armstrong on the moon less than a decade after Gagarin, and computers were becoming common place
just a few years after Kilby and Noyce dreamed up the integrated circuit. The future envisioned from the perspective of the 1960s was
hard to get to, but not impossible, and people were willing to entertain the idea. We now laugh at the Nucleon and Pan Am to the moon
while applauding underpowered hybrid cars and Easyjet, and that’s sad. The future that people in the 1960s hoped to see is still the future
we’re waiting for today, half a century later.. Instead of Captain Kirk and the USS Enterprise, we got the Priceline Negotiator and a cheap
flight to Cabo.
There are major exceptions: as we’ve seen, computers and communication technologies advanced enormously (even if Windows 2000 is a
far cry from Hal 9000) and the Internet has evolved into something far more powerful and pervasive than its architects had ever hoped
for. But a lot of what seemed futuristic then remains futuristic now, in part because these technologies never received the sustained
funding lavished on the electronics industries. Commercializing the technologies that have languished seems as good a place as any to
start looking for ideas.
3. The Internet is one of the most revolutionary technologies ever developed. If all we ever used x-rays for was in shoe shop f luoroscopes, we would be tempted to dismiss X-rays as
infertile and irrelevant. The Internet cannot be judged on the follies of the late 90s alone.
4. And then there are the matters of conscience and reputation.
3. A E R O S PA C E & T R A N S P O R TAT IO N
In 1961, Alan Shepard became the first American in space. In 1969, Neil Armstrong became the first person on the moon. We have not been
back to the moon since 1972 and with the final Shuttle flight in 2011, the US will be without the ability to send an astronaut into orbit for
the first time since it began its manned space program. For an industry that supposedly defines the future, space isn’t doing so well.
One of the major barriers to making use of space is the sheer cost of getting material into orbit: about $19,000 per kilogram (depending on
the orbit), a price that has hardly changed since the 1960s. The elasticity of demand for getting into space at very high price ranges looks
basically flat – people who have to go, go (the government, telecommunications providers), and almost no one else chooses to. Were prices
to decline, the economic potential of space could be more fully realized. Imagine if it cost you $500 every time you drove to the Apple
store. You’d be inclined to replace your computer and phone much less frequently, even though these devices get radically better every
year. If there were a vastly cheaper way of getting to Best Buy – or work, the gym, or wherever – you’d consume more of that good.
It strikes us then that finding ways to get launch costs down is not only lucrative in its own right, but would vastly increase the size and
potential of the space industry, a latter day version of the railroads opening up the West. NASA believes that the commercial market
would increase substantially were launch costs reduced by a rough order of magnitude. SpaceX appears to be on track to reduce costs by
that order of magnitude, which would make it an enormously valuable company in its own right. If it succeeds, there should at last be
plenty to do in space, from telecommunications to power generation to high-precision microgravity fabrication – if investors with cash
are ready to fund that innovation.
4. Another major area of improvement is overcoming the tyranny of distance. Cheaper, faster transportation has been a major lubricator of
trade and wealth creation. For almost two centuries, technology has improved transportation relentlessly. Unfortunately, over the past
thirty years, there have been no radical advances in transportation technology (in-flight DVD units are nice, but not revolutionary); take,
for example, the travel time across the Atlantic which, for the first time since the Industrial Revolution, is getting longer rather than shorter.
B IO T E C HN O L O G Y
Medicine has been the beneficiary of two radical developments over the past sixty years: the discovery of the structure of DNA in 1952
and the rise of information technologies in the 1960s. One would expect that the discovery of life’s code, combined with the power of
computing, would have radically increased the quality and length of human life-spans. But life-spans aren’t getting longer as quickly as
they used to, and in some places they’re even getting shorter. Worse, the number of new drugs introduced each year – especially important
new drugs (which you can measure by FDA fast-tracking) – is surprisingly low and well below the quarter-century average. 1
That’s not to say that biotechnology can’t progress quickly. Less than twenty-five years after Watson and Crick published the structure
of DNA, venture capitalist Robert Swanson and biochemist Herbert Boyer founded Genentech, which went on to synthesize insulin
far faster and more cheaply than almost anyone believed possible. And in a great revolution in the FDA approval process in the 1980s
following pressure from the AIDS lobby, the agency acted almost nimbly to approve a huge number of important new drugs for many
maladies. But the revolution in innovation and regulatory efficiency has not been sustained.
Biotechnology has already created one revolution. It can certainly create another. There are presently three major and related obstacles
facing biotechnology (or biotechnology investment at any rate): lack of data, capital intensity, and a medieval approach to therapeutic
discovery. The first major problem is that genetic sequencing, which provides us with the body of knowledge we require to create genomic
therapies, is extremely slow, expensive, and inaccurate. Present methods of sequencing (which use fluorescence) can only sequence about
95% of larger genomes, take forever to do so, and cost a fortune. The second problem is capital intensity: it simply takes far too much time
and money before a company has any real indication that a drug might work with animal/human trials fantastically expensive despite
the help of computer modeling. The final problem is an extremely slow drug discovery process: fundamentally, discovery still proceeds
by enlightened guesswork, rather than as a disciplined process – and there is no good way for investigators to share data. Biotechnology
companies that can overcome these stumbling blocks will create enormous value for their investors and society. 2
1. It’s a tricky thing to measure medical progress. Life-span doesn’t ref lect quality of life (surely we would view medicine as more advanced were we to live only 75 excellent years
rather than 80 years with 20 of them in misery) and it tends to be overdetermined by infant mortality (but note that both life-expectancy at birth, and years remaining for those
who survive to adulthood, suggest that medical progress is mediocre).
2. It’s true that government has not always been the most nimble partner; however, it is the job of new companies to overcome existing obstacles, as they have always done.
5. A D VA N C E D M A C HINE S / S O F T WA R E
The exponential growth of computational power (represented by Moore’s law), storage capacity (Kryder’s law), data transmission
(e.g., Butters’ law), and other physical embodiments of computing is familiar. What is equally familiar is the somewhat slower rate of
development in the utility of computers – software has gotten more powerful, but the rate of improvement doesn’t seem to be as swift
as in hardware, though measuring improvements in software is somewhat impressionistic. Nevertheless, as anyone who has used a
Bloomberg or Lexis can attest, the amount of data we collect clearly outstrips our ability to make easy use of it. One way to look at this
is to compare increases in computing power (as measured by the density of transistors on a chip) versus the change in productivity. Few
technologies have ever improved as quickly and consistently as computer processors and yet the impact of computing in the (admittedly
wildly overdetermined) productivity statistics is difficult to detect. This suggests that however fast hardware improves, software might
be running behind. We certainly don’t have anything approaching a general artificial intelligence, a lack many futurists 30 years ago
would have found rather surprising. Indeed, until fairly recently, it was difficult to find a stable operating system.
At the least grandiose level, we need analytical software much more powerful and much easier to use than the current state of the art.
Most analytical platforms are exceedingly arcane, requiring lengthy experience with that exact platform to acquire mastery, and yet the
quality of analysis remains fairly poor. It does society no good to collect huge amounts of data that only a small minority can analyze,
and even then only partially.
Moving up an order of difficulty, robotics represents another area of underachievement. Industrial robots can be very good at what they
do (welding car parts, e.g.), but are extremely expensive and of limited versatility. At the highest end, the industry remains over-focused
on producing vanity robots with hyper-specific capability – clunky simulacra that play the violin or smile pointlessly – rather than
solving more general problems, like locomotion. And few manufacturers are devoted to making commodity-like robots at low price points,
which is essential to a genuine robotic revolution. 1
True general artificial intelligence represents the highest form of computing. Whether and when a general artificial intelligence arrives
is less critical for the near future than whether we are able to create machines that can replicate components of human intelligence – as
we are now doing reasonably well with voice recognition and hopefully will be able to do with visual pattern recognition. At a higher
level, machine learning also represents another compelling opportunity, with the potential to create everything from more intelligent
game AIs to Watson. While we have the computational power to support many versions of AI, the field remains relatively poorly funded,
a surprising result given that the development of powerful AIs (even if they aren’t general AIs) would probably be one of the most
important and lucrative technological advances in history.
1. There are fewer than a million industrial robots, most of which reside in Japan, a country whose demographic constraints dispose it to see robots more as necessities than
other advanced nations.
6. E NE R G Y
The correlation between wealth and energy use is extremely high and whichever direction the causality runs, a future world of greater
material comfort is going to be one that uses more energy (certainly in the aggregate). Unfortunately, conventional sources of energy
are extremely problematic, tangled up with political and environmental costs, and in the case of oil, significant geologic constraints.
Alternative sources of energy represent a tremendous opportunity, but as the persistently rising real cost of energy shows, we have made
little progress in generating more energy more cheaply. 1
A lot of money has poured into clean technologies. Investments that have focused on efficiency improvements have done well as a
financial matter, but investments in alternative technologies for actually generating energy have not produced particularly good returns.
We believe that this is because many companies pursue the wrong model – they seek to be almost as good as the default product, rather
than (as should be the case generally) so much better than the default that customers will rush to switch. Imagine, if you will, if Amazon.
com were somewhat less convenient than going into, and offered similar prices to, a bricks-and-mortar store. Would you use it? Probably
not – people only flocked to Amazon when it became substantially better, in selection and convenience, than physical retailers. What
we need are companies developing sources of energy that are as good as, or better than, conventional sources at lower prices and at
scale. Unfortunately, relatively few companies research such sources, preferring instead incremental improvements on long-established
alternative technologies (wind, solar) whose physical limitations mean they cannot satisfy these requirements. But there is no reason to
believe that we can’t invent an alternative to alternatives.
1. Rising energy costs can ref lect many factors, including the internalization of externalities, but as a general matter, real progress would result in a downwardly sloped curve
even so, either because new sources of energy were cheaper or because they came with fewer externalities, or preferably, both.
7. T HE IN T E R NE T
It’s become fashionable among VCs to say that the Internet is dead, paradoxically even as venture portfolios become more and more
concentrated in the same few consumer internet companies (and their clones). The problem with web-bashing, of course, is that the
Internet is one of the most powerful technologies ever created and the idea that we have exhausted its potential two decades after
we started exploiting it commercially is as ridiculous as saying that there was nothing left to do with electricity after the light bulb.
Companies like Facebook, Spotify, and YouTube demonstrate that there is life after pets.com. Advances in cloud and other computing
technologies radically reduce the costs of starting and running new businesses, creating opportunities for even larger returns.
As a general matter, Internet companies that will outperform are the companies that take the Internet seriously – as a technology for
transferring information on a scale and at a level of convenience that can’t be replicated elsewhere – and that have a plan for translating
those advantages into cash. They probably won’t look anything like the companies that exist today; all great companies, internet and
otherwise, tend to be sui generis.
O T HE R S
Our list is by no means exhaustive. The best companies create their own sectors. As a general matter, the most promising companies (at
least from our perspective as investors) tend to share a few characteristics:
01. They are not popular (popular investments tend to be pricey; e.g., Groupon at so many dozens of billions).
02 . They are difficult to assess (this contributes to their lack of popularity).
03 . They have technology risk, but not insurmountable technology risk.
04 . If they succeed, their technology will be extraordinarily valuable.
We have no idea what these companies might look like, only that they probably will share these characteristics. Entrepreneurs often
know better than we do what might be enormously valuable in the future.
Not All Real Technology Companies Make Serious Money
Often, even great technologies fail to earn the inventors or investors a return (see, e.g., Nikola Tesla). In our experience, it really does
matter who runs the business, because the world does not beat a path to the door of the better mousetrap. Shockley Semiconductor,
Fairchild Semiconductor, and Intel all successfully resolved roughly similar technical problems, but only Intel truly prospered – poor
management consigned the other two to “also-ran” status. 1
Technology matters, but so do teams.
A curious point: companies can be mismanaged, not just by their founders, but by VCs who kick out or overly control founders in
an attempt to impose ‘adult supervision.’ VCs boot roughly half of company founders from the CEO position within three years of
investment. Founders Fund has never removed a single founder – we invest in teams we believe in, rather than in companies we’d like to
run – and our data suggest that finding good founding teams and leaving them in place tends to produce higher returns overall. Indeed,
we have often tried to ensure that founders can continue to run their businesses through voting control mechanisms, as Peter Thiel did
with Mark Zuckerberg and Facebook. This approach, we believe, accords with common sense. No entrepreneur, however good, knows
precisely how their company’s business model will evolve over time. When investing in a start-up, you invest in people who have the
vision and the flexibility to create a success. It therefore makes no sense to destroy the asset you’ve just bought.
1. Many of the also-rans still made some money even though they were grotesquely mismanaged (e.g., William Shockley tried to subject his employees to lie detector tests,
constantly changed his mind, was prone to paranoia, etc.), which shows just how far solving hard problems can go. Companies solving less difficult problems have narrower
leeway: if a me-too social gaming site is even moderately mismanaged, it’s likely to go down the toilet, because anyone can replicate the technology and so management
matters all the more.
8. As a corollary, it makes no sense to shackle a company to the Procrustean bed of its original business model. Businesses really do evolve
over time and changing models in the early years is anything but a sign of weakness. PayPal went through five different business models
before arriving at one that worked. We do not expect that the first business model for a company will be the final or best business model
and do not see evolution as a negative. The most powerful minds are the ones that can be changed.
Swinging For The Fences Is Probably Less Risky Than People Think
VC usually depends on a few runaway hits to drive returns, supplemented with a few smaller successes and a lot of failures. It seems
unlikely, as a general proposition, that a company with limited ambitions will evolve into a runaway hit – i.e., a company that aspires to
crank out a single app for the iPhone probably never turns into an Oracle. So we need to invest in at least some ambitious companies –
but how many? Our answer is that substantially all of the capital in our portfolio should be directed to companies with audacious vision
seeking enormous markets.
Several factors command that conclusion. First, plenty of capital already pursues companies with more moderate ambitions and a lower
(perceived) degree of risk. This tends to push up valuations for those companies and correspondingly depresses returns – which, of course,
increases overall portfolio risk. Also, less ambitious firms, almost by definition, do not change the world and we believe our purpose as
venture capitalists is to earn an attractive return by funding positive transformation.
Another, paradoxical reason, is that companies pursuing transformational ideas are somewhat likelier to succeed in them than less
ambitious companies. A company with a readily obtainable goal (checkers, for the iPhone!) lacks a technological barrier to entry because,
of course, the original problem was easy. And their end markets are typically quite limited, meaning that they may not achieve the
scale necessary for exit. But most importantly, we believe the brightest and most creative problem solvers seek the hardest and most
interesting problems, and gathering the best technical talent is obviously a major competitive advantage.
The Vision Thing
This brings us to another counterintuitive point: the best founders want to radically change the world for the better. To many investors,
visionary entrepreneurs come off as naïve or worse – isn’t it safer/easier/more profitable to create a(nother) social network for cat
fanciers than to try to cure cancer, defeat terrorism, or organize the world’s information? The problem is that all start-ups are difficult
– long hours, low pay, and fierce competition wear on even the most dedicated teams. The entrepreneurs who make it have a near-
messianic attitude and believe their company is essential to making the world a better place. It doesn’t matter whether everyone agrees
with the entrepreneur about the world-historical nature of the project – if the entrepreneur seeks an impact beyond his own payday
and can convince employees of the same, the project is much more likely to get done. The engineers at SpaceX are passionate about
commercializing and colonizing space; profit is a significant byproduct of their extraordinary effort to achieve that goal but not enough
to get them to pull the thousandth all-nighter. The same is true of Jobs at Apple, or the programmers at Palantir, or the researchers at
new drug companies. Early in a company’s life, an entrepreneur can make enough money to satisfy his own needs (though often not much
of a return for the investor); to take a company from $50 million to $50 billion requires singular vision and dedication. Wild-eyed passion
is not a bad thing by any means.
It Pays To Be Different
People frequently say that contrarian investments outperform conformist investments. Is that true? It’s difficult to make the case
directly, but the indirect evidence is suggestive: as we’ve seen, whatever the bottom 80% of the VC industry is doing now is losing money
for investors. Clearly, the mainstream VC model does not work very well. (Even if it did, the problem with consensus investments is that
their prices reflect broad agreement, so even if they work, they tend to produce unspectacular returns. That is not the present problem, of
course, because the consensus doesn’t work at all).
And what does it mean to be contrarian? It does not mean simply doing the opposite of what the majority does – that’s just consensus
thinking by a different guise, a minus sign before the conventional wisdom. The problems of reactive contrarianism are the same as those
9. of following the herd. The most contrarian thing to do is to think independently. It is not without its risks, because there is no cover from
the crowd and because it frequently leads to conclusions with which no one else agrees.
Investing in companies doing things that are breathtakingly new and ambitious is provocative. It is not what our industry is best at
doing, at least, not in the past decade. And there is no way to assure a positive return – but at least it has a chance of working. Simply
doing what everyone else does is not enough.
You Have To Run The Experiment
There are unknowables. Venture investments mature over long periods and there are many confounding variables, from variable
economic conditions to a shifting legal landscape – everything is overdetermined. Venture is a secretive industry and legal strictures
cramp down on disclosures. We have data that suggests what doesn’t work (the status quo) and implies what might. But we have no direct
evidence for the proposition that we ought to be investing in smart people solving difficult technical problems. In this sense, we are in
the same position as our companies, which also operate with imperfect information. SpaceX had three failed launches before making
history with its fourth. PayPal went through five business models before it found something that worked, and the history of Facebook’s
initiatives is by no means an unalloyed record of success. Still, you have to run the experiment.
We do believe that our method should outperform, and we also believe it’s the shortest route to social value. So, we will continue to invest
in very talented entrepreneurs who are pursuing ambitious, challenging tasks. We will treat them with respect and hope for the best.