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When Google unveiled Stadia, its cloud-based streaming games platform, it showed off a button on the controller that linked directly to its Google Assistant AI helper. The idea is that players will be able to easily pull up tips and relevant informat…
Carbon dioxide emissions, one of the main contributors to the climate changes bringing extreme weather, rising oceans, and more frequent fires that have killed hundreds of Americans and cost the U.S. billions of dollars, are set to reach another record high in 2019.
That’s the bad news. The good news (if you want to take a glass half-full view) is that the rate of growth has slowed dramatically from the previous two years. However, researchers are warning that emissions could keep increasing for another decade unless nations around the globe take dramatic action to change their approach to energy, transportation and industry, according to a statement from Jackson.
“When the good news is that emissions growth is slower than last year, we need help,” said Jackson, a professor of Earth system science in Stanford’s School of Earth, Energy & Environmental Sciences (Stanford Earth), in a statement. “When will emissions start to drop?”
Just in: Global carbon emissions hit a new all-time high in 2019, up 0.6% from last year.
This news is shockingly important and heartbreakingly serious. Not only are we entirely failing to reduce emissions, we are making the climate emergency worse at an increasingly fast rate. pic.twitter.com/A2nasPT3lI
— Eric Holthaus (@EricHolthaus) December 4, 2019
Globally, carbon dioxide emissions from fossil fuel sources (which are over 90 percent of all emissions) are expected to grow 0.6 percent over the 2018 emissions. In 2018 that figure was 2.1 percent above the 2017 figure, which was, itself, a 1.5 percent increase over 2016 emissions figures.
Even as the use of coal is in drastic decline around the world, natural gas and oil use is climbing, according to researchers, and stubbornly high per capita emissions in affluent countries mean that reductions won’t be enough to offset the emissions from developing countries as they turn to natural gas and gasoline for their energy and transportation needs.
“Emissions cuts in wealthier nations must outpace increases in poorer countries where access to energy is still needed,” said Pierre Friedlingstein, a mathematics professor at the University of Exeter and lead author of the Global Carbon Budget paper in Earth System Science Data, in a statement.
Some countries are making progress. Both the UK and Denmark have managed to achieve economic growth while simultaneously reducing their carbon emissions. In the third quarter of the year, renewable power supplied more energy to homes and businesses in the United Kingdom than fossil fuels for the first time in the nation’s history, according to a report cited by “The Economist”.
Data and image from The Economist
Costs of wind and solar power are declining so dramatically that they are cost competitive with natural gas in many parts of the wealthy world and cheaper than coal, according to a study earlier in the year from the International Monetary Fund.
Still, the U.S., the European Union and China account for more than half of all carbon dioxide emissions. Carbon dioxide emissions in the U.S. did decrease year-on-year — projected to decline by 1.7 percent — but it’s not enough to counteract the rising demand from countries like China, where carbon dioxide emissions are expected to rise by 2.6 percent.
And the U.S. has yet to find a way to wean itself off of its addiction to cheap gasoline and big cars. It hasn’t helped that the country is throwing out emissions requirements for passenger vehicles that would have helped to reduce its contribution to climate change even further. Even so, at current ownership rates, there’s a need to radically reinvent transportation given what U.S. car ownership rates mean for the world.
U.S. oil consumption per person is 16 times greater than in India and six times greater than in China, according to the reports. And the United States has roughly one car per-person while those numbers are roughly one for every 40 people in India and one for every 6 in China. If ownership rates in either country were to rise to similar levels as the U.S. that would put 1 billion cars on the road in either country.
About 40 percent of global carbon dioxide emissions were attributable to coal use, 34 percent from oil, 20 percent from natural gas, and the remaining 6 percent from cement production and other sources, according to a Stanford University statement on the Global Carbon Project report.
“Declining coal use in the U.S. and Europe is reducing emissions, creating jobs and saving lives through cleaner air,” said Jackson, who is also a senior fellow at the Stanford Woods Institute for the Environment and the Precourt Institute for Energy, in a statement. “More consumers are demanding cheaper alternatives such as solar and wind power.”
There’s hope that a combination of policy, technology and changing social habits can still work to reverse course. The adoption of new low-emission vehicles, the development of new energy storage technologies, continued advancements in energy efficiency, and renewable power generation in a variety of new applications holds some promise. As does the social adoption of alternatives to emissions intensive animal farming and crop cultivation.
“We need every arrow in our climate quiver,” Jackson said, in a statement. “That means stricter fuel efficiency standards, stronger policy incentives for renewables, even dietary changes and carbon capture and storage technologies.”
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Like spot instances for the EC2 compute platform, Fargate Spot pricing is significantly cheaper, both for storage and compute, than regular Fargate pricing. In return, though, you have to be able to accept the fact that your instance may get terminated when AWS needs additional capacity. While that means Fargate Spot may not be perfect for every workload, there are plenty of applications that can easily handle an interruption.
“Fargate now has on-demand, savings plan, spot,” AWS VP of Compute Services Deepak Singh told me. “If you think about Fargate as a compute layer for, as we call it, serverless compute for containers, you now have the pricing worked out and you now have both orchestrators on top of it.”
He also noted that containers already drive a significant percentage of spot usage on AWS in general, so adding this functionality to Fargate makes a lot of sense (and may save users a few dollars here and there). Pricing, of course, is the major draw here, and an hour of CPU time on Fargate Spot will only cost $0.01245364 (yes, AWS is pretty precise there) compared to $0.04048 for the on-demand price,
With this, AWS is also launching another important new feature: capacity providers. The idea here is to automate capacity provisioning for Fargate and EC2, both of which now offer on-demand and spot instances, after all. You simply write a config file that, for example, says you want to run 70% of your capacity on EC2 and the rest on spot instances. The scheduler will then keep that capacity on spot as instances come and go, and if there are no spot instances available, it will move it to on-demand instances and back to spot once instances are available again.
In the future, you will also be able to mix and match EC2 and Fargate. “You can say, I want some of my services running on EC2 on demand, some running on Fargate on demand, and the rest running on Fargate Spot,” Singh explained. “And the scheduler manages it for you. You squint hard, capacity is capacity. We can attach other capacity providers.” Outpost, AWS’ fully managed service for running AWS services in your data center, could be a capacity provider, for example.
These new features and prices will be officially announced in Thursday’s re:Invent keynote, but the documentation and pricing is already live today.
Private equity and venture capital investors are copying our counterparts in the hedge fund world: we’re trying to automate more of our job.
When I was single, I registered for (a lot of) dating websites. When I met my now-wife, I realized that any technology that can find me a spouse is a killer app. That’s why 40 million Americans use online dating sites. But, most of use raise capital and source deals the same way people looked for dates 20 years ago: networking at conferences (or bars).
Most of us want one spouse and we’re done, but in business, you want a lot of partners. I’d argue that the same type of technologies that have revolutionized dating can revolutionize our industry.
In liquid markets, most of the calories expended on technology and analytics are focused on trade selection, or “origination.” However, in private markets, there is more room to optimize across all 11 steps of the investing process. Below, I’ll walk through how progressive investors are using technology and analytics throughout all of their operations. To learn more about this space, I suggest joining an online community I co-founded, PEVCTech.
1) Managing the firm
Before you can actually invest, you have to manage your fund. This is harder than it sounds. In the private equity universe, most partners have primary training as deal-makers, not as managers. When I talk with junior personnel at private equity firms, the quality of firm management is a frequent complaint.
I’ve used Asana extensively to manage activities firm-wide. I also use several living Google docs to maintain the minutes and the group agendas for my fixed weekly meetings. I use another live Google doc to maintain my database of companies I’m marketing to other VCs. That Google document provides cut and pasteable text I can share with other investors, based on their stage, focus and appetite.
Other investors use Trello, Basecamp, and Monday for making sure that everyone at the firm knows each others’ long-term OKRs and short-term projects. Point Nine Capital uses 15Five for continuous employee feedback.
One aspect of management which merits attention is your own cybersecurity, which should not be left until a crisis to address. Small investment firms often have interns and entrepreneurs in residence passing through, each of which is a security risk. (See A comprehensive guide to security for startups by Bessemer Ventures.)
Kyle Dunn, CEO of Meyler Capital, says “investors should focus on building a large audience within a CRM system (having the ability to categorize your different constituents); communicate consistently to that audience; and implement an automation platform that can leverage lead score to profile interest. It sounds simple; however, very few asset managers actually do it.” I agree.
Many tools designed for B2B marketing in general are also relevant to investors. I know of funds using Constant Contact, Goodbits, Pardot and Publicate to create light newsletters for internal and external consumption. A major angel group uses Influitive, an advocate management tool, to track, activate and motivate their members. Other VCs use Contently* or Social Native* to create relevant content. Meyler Capital is taking the analytical rigor of modern internet marketing and applying it to fund marketing.
Point Nine Capital’s website is now powered by Contentful — it uses Unbounce for landing pages and Typeform for surveys and other data collection. “We’re using … TinyLetter for our “Content Newsletter” … and Buffer to schedule social media posts. Last but not least, we still use MailChimp to publish our (in)famous newsletter.” I also use Mailchimp for the teten.com and pevctech.com mailing lists. Point Nine Capital uses Mention for media monitoring. Teten.com is built on WordPress as my content management system.
I use Hootsuite to coordinate my social media activity, which consists of Teten.com, PEVCTech.com, Linkedin, AngelList, and (passively) Twitter and Facebook. I use Google Drive to host my conference presentations, which are all embedded at teten.com. I use Diigo, a social bookmarking tool, to keep a record of useful websites. I have also configured IFTTT to share on Twitter anything new I post on Diigo.
“There are two crucial aspects of marketing that investors often overlook: automation and analytics,” wrote Sabena Quan-Hin, Marketing Manager at Flow Capital. “Automation allows you to spend less time on tedious tasks and will help boost productivity, especially within a small marketing team. At Flow Capital, we use HubSpot’s sequences and workflows functions to automate a bulk of our emails and internal tasks. This provides us more time to develop meaningful relationships with prospects and customers. We use Google Analytics, HubSpot, and LinkedIn Campaign Manager for the majority of our analytics. For our content creation, we use tools such as Canva (graphic design) and GoToStage (webinars platform) to create and share content for prospects to find.”
3) Raising capital
Tim Friedman, Founder, PE Stack, said, “If I could offer one piece of advice to today’s managers, it would be to take the time to understand the demands of the modern institutional LP. Today’s investors are allocating more to alternatives in an environment where there are record numbers of new funds; and seeking deeper relationships with managers via direct and coinvestments. The past few years have therefore seen a huge rise in the proportion of LPs using specialized tools to manage and understand their portfolios, including platforms such as Chronograph, Solovis, Allocator, Cobalt LP, eFront Insights, iLevel, Burgiss.
The proportion of LPs using technology to manage their portfolios will continue to increase, and GPs unable to provide quality data to LPs will find it increasingly hard to retain and attract LPs. We are also seeing technology evaluation as an increasingly important part of LP operational due diligence. Excel and Google simply aren’t going to cut it if you expect to build a high quality institutional investor base.”
A more efficient approach to fundraising than haphazard networking is to mine the data exhaust from the limited partner universe to identify those LPs most likely to find your fund attractive and focus all your energy on them. I previously posted a detailed presentation with sales technology tools useful for B2B sales.
I always make a point of keeping firm records updated in the major data-trackers tracking the VC industry: AngelList, CB Insights, Crunchbase, Dow Jones VentureSource, Pitchbook, Preqin, and Refinitiv Eikon. LPs, coinvestors, and press use these tools, so I work for free for these data vendors to make sure that their data about our activities is correct. This is a great example of why data businesses have substantial moats.
Boardex and Relationship Science make it easier to understand and map social networks into potential limited partners. Cobalt for General Partners helps GPs to optimize their fundraising strategy. MandateWire and FinSearches provide leads on limited partners with new mandates which might fit your fund. Evestment is a platform for capital-raisers; Evestment TopQ automates private markets performance calculation.
I am a heavy user of DocSend, a secure content sharing and tracking platform that can be used to seamlessly share recurring materials with potential LPs. It provides analytics to track shared materials across target senders and improve the content for future leads. Point Nine Capital uses Qwilr to create modern, mobile-native collateral.
Most funds open data rooms to share previous reports, performance data, pitch decks, legal docs and other fundraising material with LPs. I’ve seen funds using Ansarada, Allvue, Box, CapLinked, dfsco, Dropbox, Digify, Drooms, Google Drive, iDeals, Intralinks, Ipreo, Merrill Corporation, and SecureDocs for their Virtual Data Rooms. These same tools are used by companies raising capital.
I’ve also experimented with using services which are marketplaces between LPs and GPs: CEPRES, DiligenceVault, FundVeil, Harvest Exchange, and Palico. Some funds are using technology-enabled intermediaries to help them sell to retail LPs, e.g., Artivest and iCapital Network.
Deer Isle Group has built the D.I.G. Beacon technology system, which automatically outbound-solicits a universe of over 10,000 institutional investors, without requiring LPs to register for an online network of funds.
Figuring out just what an AI is good at is one of the hardest thing about understanding them. To help determine this, OpenAI has designed a set of games that can help researchers tell whether their machine learning agent is actually learning basic skills or, what is equally likely, has figured out how to rig the system in its favor.
It’s one of those aspects of AI research that never fails to delight: the ways an agent will bend or break the rules in its endeavors to appear good at whatever the researchers are asking it to do. Cheating may be thinking outside the box, but it isn’t always welcome, and one way to check is to change the rules a bit and see if the system breaks down.
What the agent actually learned can be determined by seeing if those “skills” can be applied when it’s put into new circumstances where only some of its knowledge is relevant.
For instance, say you want to learn if an AI has learned to play a Mario-like game where it travels right and jumps over obstacles. You could switch things around so it has to walk left; you could change the order of the obstacles; or you could change the game entirely and have monsters appear that the AI has to shoot while it travels right instead.
If the agent has really learned something about playing a game like this, it should be able to pick up the modified versions of the game much quicker than something entirely new. This is called “generalizing” — applying existing knowledge to a new set of circumstances — and humans do it constantly.
OpenAI researchers have encountered this many times in their research, and in order to test generalizable AI knowledge at a basic level, they’ve designed a sort of AI arcade where an agent has to prove its mettle in a variety of games with varying overlap of gameplay concepts.
The 16 game environments they designed are similar to games we know and love, like Pac-Man, Super Mario Bros., Asteroids, and so on. The difference is the environments have been build from the ground up towards AI play, with simplified controls, rewards, and graphics.
Each taxes an AI’s abilities in a different way. For instance in one game there may be no penalty for sitting still and observing the game environment for a few seconds, while in others it may place the agent in danger. In some the AI must explore the environment, in others it may be focused on a single big boss spaceship. But they’re all made to be unmistakably different games, not unlike (though obviously a bit different from) what you might find available for an Atari or NES console.
Here’s the full list, as seen in the gif below from top to bottom, left to right:
- Ninja: Climb a tower while avoiding bombs or destroying them with throwing stars.
- Coinrun: Get the coin at the right side of the level while avoiding traps and monsters.
- Plunder: Fire cannonballs from the bottom of the screen to hit enemy ships and avoid friendlies.
- Caveflyer: Navigate caves using Asteroids-style controls, shooting enemies and avoiding obstacles.
- Jumper: Open-world platformer with a double-jumping rabbit and compass pointing towards the goal.
- Miner: Dig through dirt to get diamonds and boulders that obey Atari-era gravity rules.
- Maze: Navigate randomly generated mazes of various sizes.
- Bigfish: Eat smaller fish than you to become the bigger fish, while avoiding a similar fate.
- Chaser: Like Pac-Man, eat the dots and use power pellets strategically to eat enemies.
- Starpilot: Gradius-like shmup focused on dodging and quick elimination of enemy ships.
- Bossfight: 1 on 1 battle with a boss ship with randomly selected attacks and replenishing shields.
- Heist: Navigate a maze with colored locks and corresponding keys.
- Fruitbot: Ascend through levels while collecting fruit and avoiding non-fruit.
- Dodgeball: Move around a room without touching walls, hitting others with balls and avoiding getting hit.
- Climber: Climb a series of platforms collecting stars along the way and avoiding monsters.
- Leaper: Frogger-type lane-crossing game with cars, logs, etc.
You can imagine that an AI might be created that excels at the grid-based ones like Heist, Maze, and Chaser, but loses the track in Jumper, Coinrun, and Bossfight. Just like a human — because there are different skills involved in each. But there are shared ones as well: understanding that the player character and moving objects may have consequences, or that certain areas of the play area are inaccessible. An AI that can generalize and adapt quickly will learn to dominate all these games in a shorter time than one that doesn’t generalize well.
The set of games and methods for observing and rating agent performance in them is called the ProcGen benchmark, since the environments and enemy placements in the games are procedurally generated. You can read more about them, or learn to build your own little AI arcade, at the project’s GitHub page.
Noted Silicon Valley venture capital fund Sequoia Capital has raised nearly $1 billion for later-stage U.S. investments and roughly $2.4 billion for venture and growth deals in China, according to paperwork filed with the U.S. Securities and Exchange Commission on Tuesday.
The firm, famous for its investments in U.S. companies like Google, Instagram, Dropbox, LinkedIn, Snap and WhatsApp, is also an investor in some of China’s most successful startups.
These are companies like Alibaba, China’s e-commerce answer to Amazon; Ant Financial, a multibillion-dollar financial services powerhouse; JD.com, another e-commerce powerhouse; ByteDance, the owner of America’s latest social media sensation, TikTok; and Yitu, one of the national leaders in the development of machine learning applications.
These investments have not come without their share of controversy abroad. Yitu has been linked to the technology dragnet currently in place in Xinjiang, where an estimated 1 million religious and ethnic minorities are currently interned. Meanwhile, TikTok’s popularity in the U.S. has come with accusations of censorship in its treatment of posts that were supportive of both Xinjiang’s imprisoned population and the dissidents protesting mainland China’s increasing control over Hong Kong politics.
Setting politics aside, Sequoia has brought in $1.8 billion for its Sequoia Capital China Growth Fund V and about $550 million for Sequoia Capital China Venture Fund VII, per filings with the Securities and Exchange Commission.
It’s a sign that when valuations are concerned (ByteDance alone is now worth $78 billion, according to some reports), investors can overlook the potential political pitfalls of dealing with China.
Sequoia, led by Doug Leone, Michael Moritz, Roelof Botha and others, recently sought $8 billion for a global fund, its largest-ever fundraise, holding a first close of $6 billion in June 2018. In addition, the firm operates Sequoia Capital India, with offices in Menlo Park, Bengaluru, Mumbai, New Delhi, Singapore, Tel Aviv, Beijing, Hong Kong and Shanghai.
News of the fund comes at the tail end of another strong year for venture capital fundraising in the U.S. Firms, including 41-year-old NEA, filed to raise as much as $3.6 billion for a single fund. Meanwhile, Norwest Venture Partners, DCVC and Accel all closed new vehicles exceeding $500 million.
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