ESG for the Short Seller with Alt Data
Short-selling opportunities exist using ESG Alternative Data
Data Sets
Data sets drive the quantitative researcher. Standard data sets, like historical market data, and alternative data sets, like social sentiment, allow the quant to search for trading signals in the data.
Posts
Environmental, Social, and Governance Data December 30, 2019
In our study of Environmental, Social, and Governance (ESG) data, we looked at holding positions based upon the G&S Quotient short term price predictor score. We found that 5-day holds and 20-day holds using this score were very interesting and produced positive returns. Based on this data set we saw that you could have traded and held some of these stocks and closed your positions at the end of the day last Friday. See the charts for $ADBE, $AAPL, $MSFT, and $LDOS
Environmental, Social, & Governance (ESG) Short Term Trading
Short-term ESG data is showing some very interesting opportunities. Our recent whitepaper shows that 5-day and 20-day positions are profitable.
Spot checking the white paper shows the following simulated trades from last week.
The simulated trades were MOO on Monday, MOC on Friday.
$ADBE ESG Simulated Trading, 5 Day Hold
$DE ESG Simulated Trading, 5 Day Hold
$FOX ESG Simulated Trading, 5 Day Hold
CloudQuant Proves the Value in Environmental Social and Governance Alternative Data
CloudQuant LLC has proven the value in the G&S Quotient Environmental, Social, and Governance (ESG) alternative dataset. The detailed data science study shows a long-short portfolio with a five-day or twenty-day position holding period produces an investment strategy with single year Sharpe Ratios as high as 2.046 and Alphas as high as 5.24%. The study shows that the dataset is highly distinct from other standard and so-called “smart-beta” factors.
Fintech Capital Markets on CloudQuant’s AI push adds RavenPack for alt-data
CloudQuant’s CEO recently discussed the addition of RavenPack analytics to our trading strategy incubator with Fintech Capital Markets at the Battle of the Quants conference in London.
Topics covered:
- Alpha Signal Studies
- Professional level technology for the crowd to compete with Wall Street
- Bitemporal data access for historical data
- Alternative Data
Conversations: Effects of Alternative Data Sets on Trading Algorithms
What effect can alternative data sets have on trading algorithms?
We asked a few of our teammates and systematic traders what the effect of alternative data sets is on trading algos. We thought we could spread some insight as to why our alternative data is so valuable the also developers. We all start using the smallest and most basic data sets, such as the generic S&P500 stock prices. This is all just fine until you want to take your development to the next level. You can delve deeper into predicting the rise and fall of each stock using these specified alternative data sets. CloudQuant offers a wide and expanding variety of these data sets for free, giving our users easy access to alternative data in order to help them improve their trading strategies. The teammates featured are:- Tayloe Draughon- Sr. Product Manager
- James Chang- Quantitative Portfolio Manager
- Morgan Slade- CEO
- Steve Pettinato- Portfolio Manager
- Paul Tunney- Client Success Manager
Backtesting Trading Strategies
If you knew your trading strategy would work 50% of the time, would you commit your scarce savings to trade it? What if it worked 75% of the time? Backtesting gives one the confidence to know that your trading strategy will work.
Futures Radio Show interviews Morgan Slade December 12, 2017
CloudQuant’s CEO was interviewed by Anthony Crudele of Futures Radios show to discuss topic including Artificial Intelligence, Machine Learning, and Deep Learning applied to algorithmic trading. Alternative datasets are a major topic of discussion. People are saying that data is being created faster than ever before. That really isn’t true. What is really happening is that data is being captured and stored at a faster rate than ever before. Vendors are now making AltData available for traders to change the way that they interact with the markets. This applies to futures and stocks with the popularity of Deep Learning in algorithmic trading strategy development.
Industry News: Machine Learning and Artificial Intelligence for December 18, 2017
Generational Tech Shift to Transform Trade Lifecycle
…tion of new technologies. As global financial markets continue to evolve, the real opportunities are yet to be delivered in transparency and efficiency for investors.” Distributed ledger technology, machine learning, portfolio optimisation techniques and the cloud are being used today but the paper said the challenge for markets and policy-makers is to harness this potential while managing its new risks. “Neither legacy systems nor policy inertia should be allowed to stifle this generational opportunity,” added NEX. Mark Whitcroft, founding partner at venture capital firm Illuminate Financial Management, s… 2017-12-15 06:39:54+00:00 http://marketsmedia.com/generational-technology-shift-transform-trade-lifecycle/ CloudQuant Thoughts: We really like the following quote in this article:“A huge part of financial services built technology in-house or used a small number
of vendors and that old model is dying,” Whitcroft added. ‘Financial services is being componentisized.”
This gets to the heart of new business models that include innovation and crowdsourcing. We have found that innovators, with atypical backgrounds and education, when given access to institutional grade tools and datasets can create something unique. There is significant value that can be derived. Our business model is proving this out daily.
Deutsche Bank Upgrades Equities Trading With AI
…Deutsche Bank today announced the implementation of an upgraded equities trading platform with artificial intelligence (“AI”) capabilities, setting a new benchmark for best execution, a key focus for financial institutions ahead of MiFID II. Under MiFID II, financial institutions will have to demonstrate they have taken sufficient steps to obtain the best possible result when executing client orders. Using a unique combination of next-generation algorithms, Deutsche Bank’s enhanced equities trading platform is o… 2017-12-14 11:02:41+00:00 http://marketsmedia.com/deutsche-bank-ai-upgrade-equities-trading/ CloudQuant Thoughts: Innovation on the sell side to provide brokerage capabilities is always welcome. So much of the sell side innovations have been the integration of vendor technologies as demonstrated by the rapid growth of technology like Fidessa into the listed derivatives market and new vendors like Vertex Analytics. DB’s Autobahn has a good reputation among the fund managers who utilize it for research and trade execution. DB’s claim that “Autobahn 2.0 will also help us to reduce technology risk and save costs for our clients” may be a bit optimistic though. The growth of internally developed systems inside the sell-side is sometimes dangerous if the firm does not keep a strong focus on meeting the continued needs of the buy-side. Sometimes this is difficult to maintain for a longer period of time with additional risk being transferred to the buy side clients as management, engineers, and support staff turn over with the passing of time. We hope that DB’s German engineering approach won’t allow this to happen!World’s Biggest Pension Fund Sees AI Replacing Asset Managers
…: What are the biggest changes in the investment world you see coming in the next five to 10 years? Mizuno: Adoption of technology, including AI and ESG integration into all asset classes. I believe artificial intelligence will be able to either replace or enhance the asset managers’ work, particularly for short-term trading. Question: What are the implications? Mizuno: Asset managers have to adjust their conventional business model. Investors will be more focused on the long-term investment theme, as AI will take over the short-term trading. In other words, investors will shift their focus to the long-term susta… 2017-12-15 09:43:52-05:00 http://www.wealthmanagement.com/industry/worlds-biggest-pension-fund-sees-ai-replacing-asset-managers CloudQuant Thoughts: The prediction (in this article) that Amazon and Google may at some point become Fund Managers is very interesting. When you consider that they have access to huge amounts of Alternative Datasets from their core businesses there is a strong probability that they would be successful. The concern is that none of the “portal” giants have ever been above average in providing trading data. Their financial portals miss out on critical data points that FINTECH firms like Bloomberg, Interactive Data, CQG, Thompson Reuters, don’t. Amazon, Google, and others would have to go through a learning curve or acquire those skills and that focus. Fund management and trading companies run differently than other businesses.Microsoft levels up Word, Excel, and Outlook with more AI capabilities
…Microsoft is adding a host of new capabilities to its Office productivity suite that are aimed at using machine learning to help people get their work done more efficiently. Outlook, Excel, and Word will all benefit, with new features rolling out to a limited set of users in the coming months and then expanding to a broader set of people later on. Outlook’s web client will provide users with an interface that will automatically offer them responses to questions layered inside emails, while Excel has a new feature … 2017-12-13 00:00:00 https://venturebeat.com/2017/12/13/microsoft-levels-up-word-excel-and-outlook-with-more-ai-capabilities/ CloudQuant Thoughts: Excel is still one of the strongest data analytics tools.New Hedge Funds Next Year Will Embrace High Tech
…industry may be getting one step closer to its robot-guided future. Seventy percent of new hedge funds that will start next year will include investment processes that use computer models, including artificial intelligence and machine-learning technologies, according to a prediction in a Deloitte report released Thursday. That’s a jump from 47 percent in 2015. The new technologies process large, alternative data sets and hedge funds have increasingly turned to them to generate higher returns. That doesn’t mean 2018 will be easy for the industry overall. Investment firms will continue to be pressured by regulatory… 2017-12-15 00:00:00 https://www.bloomberg.com/news/articles/2017-12-15/rise-of-quant-new-hedge-funds-next-year-to-embrace-high-tech CloudQuant Thoughts: No surprise here. We used AI, and alternative data sets to launch our crowdsourcing trading strategy incubator. Others have seen success in innovating and application of technology.Trends: Rich Data or only Data Rich? Have banks figured out Big Data? | Fintech Recap 2017
…g the great mass of customer data jealously guarded in siloes, with no access or use. And when the fintechs come to the bank boards with proposals, they’re bringing the latest buzzwords in tow – AI, Machine Learning and Advanced Analytics; it’s lost on them that all those words come under the same banner. Anyone can compile a few transactions in a glorified Excel sheet, apply a few analytics and sell it off as an ‘AI enabled recommendation’ product. The term Big Data is troublesome in itself as a misnomer. Computing vast oceans of data which, in itself can be complex, does not do justice to the actual compl… 2017-12-15 00:00:00 http://www.bobsguide.com/guide/news/2017/Dec/15/trends-rich-data-or-only-data-rich-have-banks-figured-out-big-data-fintech-recap-2017/ CloudQuant Thoughts: The idea that Clean Data and Fast Data combined equal Rich Data is compelling. One used to hear terms like data mining or data research. Institutional banks need to compete. To compete they need to continue to monetize assets including data. This path to monetizing data will include working across silos to build their own internal alternative data sets for use by new business lines that have yet to be formalized within the traditional bank.Essentials of Deep Learning : Introduction to Long Short Term Memory
…te Text generation using LSTMs. 1. Flashback: A look into Recurrent Neural Networks (RNN) Take an example of sequential data, which can be the stock market’s data for a particular stock. A simple machine learning model or an Artificial Neural Network may learn to predict the stock prices based on a number of features: the volume of the stock, the opening value etc. While the price of the stock depends on these features, it is also largely dependent on the stock values in the previous days. In fact for a trader, these values in the previous days (or the trend) is one major deciding factor for predictions. … 2017-12-10 12:22:43+05:30 https://www.analyticsvidhya.com/blog/2017/12/fundamentals-of-deep-learning-introduction-to-lstm/ CloudQuant Thoughts: This article is the most technical posting included in this week’s post. It is well worthwhile reading. The concept that your trading algorithim may need to understand context from something else that happened much earlier in time sequence has a lot of very interesting applications in trading.How banks can build better engagement with business customers
…ds their financial needs well or fairly well”, 40 per cent cite a lack of personalisation as a major reason for leaving their current provider. This highlights the clear opportunity that the rise of Artificial Intelligence presents for providers to enhance and personalise the customer experience for SMEs. Chatbots, in particular, could move beyond a customer service role to one where they offer real engagement with a small business’ needs. In Sweden, Swedbank has developed a web assistant called Nina, which has an average of 30,000 conversations per month and can handle more than 350 different customer questions. … 2017-12-13 12:16:33 https://www.finextra.com/blogposting/14833/how-banks-can-build-better-engagement-with-business-customers CloudQuant Thoughts: Does anyone want to help us with our ChatBot project? We need to develop one too.15 Trending Data Science GitHub Repositories you can not miss in 2017
…siast, I have curated a list of repositories that have been particularly famous in the year 2017. Enjoy and Keep learning! Table of Contents Repositories for Learning Resources Awesome Data Science Machine Learning / Deep Learning Cheat Sheet Oxford Deep Natural Language Processing Course Lectures PyTorch – Tutorial Resources of NIPS 2017 Open Source Softwares TensorFlow TuriCreate – A Simplified Machine Learning Library OpenPose DeepSpeech Mobile Deep Learning Visdom Deep Photo Style Transfer CycleGAN Seq2seq Pix2code 1. Learning Resources 1.1 Awesome Data Science This GitHub repository is an ultimate r… 2017-12-15 00:00:00 https://www.analyticsvidhya.com/blog/2017/12/15-data-science-repositories-github-2017/ CloudQuant Thoughts: We don’t understand why they left our GitHub repository off the list. Our GitHub repository is increasingly growing with sample python trading algorithms and scripts that can be used to help trading strategy developers grow in their capabilities. You can find our repository at https://github.com/cloudquantaiWith IoT, any company can enter the SaaS market
…team generator manufacturer sells a small batch of units to a pilot customer, connecting them all through an IoT platform that exports the real-time status of more than 50 operational parameters to a machine learning model for three months. The resulting machine learning model quantifies some initial assumptions and creates some new insights for the operation usage. The steam generator company can now sell a monitoring service to new customers that improves serviceability with predictive maintenance, boosts supply chain efficiency with more accurate demand information, and lowers customer costs with demand-ba… 2017-12-16 00:00:00 https://venturebeat.com/2017/12/16/with-iot-any-company-can-enter-the-saas-market/ CloudQuant Thoughts: It is no big secret that quantitative analysts want access to the Alternative Datasets that IoT will provide. The capabilities of predicting stock movements will greatly affect trading and investment strategies.
Industry News: Machine Learning and Artificial Intelligence for December 11, 2017
Hedge funds embrace machine learning—up to a point
ARTIFICIAL intelligence (AI) has already changed some activities, including parts of finance like fraud prevention, but not yet fund management and stock-picking. That seems odd: machine learning, a subset of AI that excels at finding patterns and making predictions using reams of data, looks like an ideal tool for the business. Yet well-established “quant” hedge funds in London or New York are often sniffy about its potential. In San Francisco, however, where machine learning is so much part of the furniture the term features unexplained on roadside billboards, a cluster of upstart hedge funds has sprung up in order to exploit these techniques. These new hedgies are modest enough to concede some of their competitors’ points. Babak Hodjat, co-founder of Sentient Technologies, an AI startup with a hedge-fund arm, says that, left to their own devices, machine-learning techniques are prone to “overfit”, ie, to finding peculiar patterns in the specific data they are trained on that do not hold up in the wider world. This is especially true of financial data, … 2017-12-09: https://www.economist.com/news/finance-and-economics/21732147-investing-more-artificial-intelligence-need-not-mean-less-human CloudQuant Thoughts: Traditional hedge fund managers may be concerned with AI and machine learning. CloudQuant embraces it. We have found that the CrowdSourcing model allows for new talent to join in the research activities. A thousand researchers with access to industrial grade historical market data, backtesting tools, and alternative data can discover new ways of trading that a traditional quant at a hedge fund may not see. Our record of allocations demonstrates that this is working well for us.Demand for AI Talent Turns Once-Staid Conference Into Draft Day
Actors in robot costumes stood in the lobby of the Westin hotel in Long Beach, California on Sunday night, “Intel Inside” stickers displayed on their foam torsos. People posed for selfies before heading to an upstairs ballroom, decorated with neon purple lighting and plush white leather furniture, for an event that was more party than technology panel discussion. This was one of many attempts by Intel Corp. and other giant corporations to curry favor with artificial-intelligence researchers attending one of the world’s biggest AI conferences, turning what was once an academic event into a recruiting frenzy more akin to the National Football League’s draft day. Tech companies are increasingly competing with one another, as well as banks and hedge funds, to hire experts in AI techniques like neural networking, a kind of machine learning loosely based on how the human brain works. These are the skills behind recent advances in computers’ ability to identify objects in images, translate languages, drive cars and spot financial fraud. More changes are in store for many industries and conferences like this week’s one on Neural Information Processing Systems, aka NIPS, are where … 2017-12-06: https://www.bloomberg.com/news/articles/2017-12-06/demand-for-ai-talent-turns-once-staid-conference-into-draft-day CloudQuant Thoughts: It is fun seeing financial firms mentioned alongside the technology firms that you typically expect to see in a conference like this. Anyone in trading will fully understand that trading firms have been very technology-centric for the past decade. The introduction of Machine Learning, Deep Neural Network, and applied AI into the FINTECH discussions, and the recruiting process is not surprising.This Harvard PhD’s AI Startup Aims to Help Analysts Triple Coverage
…After applying his machine learning programs to central bank policy statements to churn out trading calls, a hedge fund-backed political economy specialist is aiming his sights on corporate earnings announcements. Evan Schnidman, a 31-year-old who set up his own firm after a Harvard University PhD dissertation that looked at the Federal Reserve’s communications, is hoping the approach that lured $3.3 million in a fund-raising roun… 2017-12-11 00:00:00 https://www.bloomberg.com/news/articles/2017-12-11/harvard-phd-s-ai-startup-aims-to-help-analysts-triple-coverage CloudQuant Thoughts: The article ends with “Demand for data scientists and machine-learning professionals in finance ‘far exceeds the current supply,‘” We see that many universities and programs are gearing up to meet this demand. Those that want to learn and practice skills are always welcome to grow their data science and machine-learning skills on our CloudQuant platform.3 Questions with Dr. Sean Wise of Ryerson Futures Seed Fund
…inancing round. What do you believe the next major innovation in financial technology will be and why? I believe the next major innovation in financial technology will be the wide integration of AI/Machine Learning into customer service chat-bots. The majority of customer service queries are mundane and routine (e.g. I lost my PIN what do I do). This is just an awful job for humans and outsourcing to developing nations has not solved it. Chatbots offer an exponentially better more scalable solution to better customer service. The volume of queries, the routineness of such and the current level of semantic … 2017-12-10 14:05:55-05:00 http://finteknews.com/3-questions-dr-sean-wise-ryerson-futures-seed-fund/ CloudQuant Thoughts: Fintek News interviewed our CEO prior to chatting with Dr. Wise. You can find and compare answers from Dr. Wise with Morgan Slade’s answers by reviewing our earlier inteview at http://finteknews.com/3-questions-john-morgan-slade-cloudquant/Hedge fund managers embrace innovation amid industry challenges and increased competition
…gin pressures by investing in technology. Forty per cent say they plan to invest in automating manual processes and more than a quarter of managers (27 per cent) have or will be making investments in artificial intelligence and robotics to strengthen their middle and back office. Zeynep Meric-Smith, EMEIA Leader, Hedge Fund Services, Ernst & Youn, says: “Managers with growing businesses will often need to add to their headcount to support the business, but modern advances in technology provide helpful solutions in supporting operating models that add to the bottom line, rather than reduce it.” The need for tec… 2017-12-08 00:00:00 http://www.hedgeweek.com/2017/12/08/259158/hedge-fund-managers-embrace-innovation-amid-industry-challenges-and-increased CloudQuant Thoughts: In this article it says “Investors are looking for managers who can effectively implement next generation data to gain an advantage, according to the survey. Managers are beginning to notice that effective use of data is a key advantage,” CloudQuant firmly believes this. Our crowd researchers are finding alpha in new ways, using new data sets. We believe that our experience is indicative for the future of most investment managers and traders.Big data solutions to take a bite out of fraud
…nd harnessing the massive quantities of data produced each day, companies hope to uncover potential fraud as it occurs. The most optimistic believe that the predictive capabilities of big data-driven artificial intelligence may someday end online crime altogether. That may well come to pass, but it will be an uphill climb. The current state of affairs The internet represents an ever-larger portion of global retail sales each year. Estimates indicate that e-commerce transactions alone will reach $2.3 trillion dollars this year. Digital platforms also generate enormous amounts of advertising revenue and related busi… 2017-12-08 11:00:34+00:00 http://bigdata-madesimple.com/big-data-solutions-to-take-a-bite-out-of-fraud/#Comment CloudQuant Thoughts: This is another article in the trend of articles talking about using AI, ML, and evolving computer tools and techniques to detect fraud. We recently posted on our blog about these tools and techniques related to Algos and Ethics. The FINTECH & REGTECH industries have been rather busy in applying AI/ML to fraud. Here are some actions and innovations that we have seen in the world of electronic trading covering regulators and vendors. AI, Algo Trading and the Regulators and Watchdogs- Improved surveillance tools and techniques being championed and shared within the industry including the Futures Industry Association’s Market Access Risk Management Recommendations best practice white paper.
- Exchange hosted and trading system mandatory pre-trade limits and speed limits (CME Globex Credit Controls, Eurex pre-trade controls, CQG, Trading Technologies, Fidessa, and more)
- New registrations and training, (like the FINRA series 99 registration for IT and operations staff)
- Regulators working with federal policing agencies to criminalize cheaters, especially spoofing. (Reference FBI and Michael Coscia of Panther Energy)
- Vertex Analytics with their amazing ability to see patterns in the market data and highlight cheaters.
- Trading Technologies’ Neurensic product that uses machine learning to catch spoofers, front-runners, layering, pump and dump, and more forms of illegal trading.
- Edge Financial Technologies and their KillSwitchPlus tool that catches run away algos and limit breaches at the time of the order.
- Catelas with its surveillance ability to catch collusion between traders or inappropriate use of insider data.
5 Scary Things That Won’t Crash the Market in Next 5 Years
…o the CFA Institute highlighted 5 disruptive forces influencing the future of global investing. I think these forces are vitally important, but will not “crash” the market in the next five years: 1. Artificial intelligence, big data and machine learning will be disruptive forces, but humans will still play an important role in providing investment management and financial advice. Quantitative algorithms are increasingly used to identify past patterns and subtle trends in large sets of data. Quantitative models may be superior to humans in looking through the rearview mirror, but humans still may be better equipped … 2017-12-04 00:00:00 http://techcenter.thinkadvisor.com/2017/12/04/5-scary-things-that-wont-crash-the-market-in-next?ref=hp-blogs CloudQuant Thoughts: We don’t consider big data, AI, or machine learning to be scary. We also agree that we don’t believe that this will be the direct cause of any future market crash.The Computer That Saved a Vineyard
… fire. He hosed down embers as they flew off the frame. Yet the winery survived the worst disaster in the history of California’s wine country unscathed, because Palmaz wasn’t alone, exactly. He had artificial intelligence on his side. Palmaz Vineyards’ winemaking takes place in an engineered maze of tunnels and domes carved into rock at the base of Napa’s Mount George. Source: Palmaz Vineyards Felix is the nickname for the Fermentation Intelligence Logic Control System (Filcs), software Palmaz engineered to analyze and, eventually, help micromanage the vineyard’s 36 winemaking tanks. Using technology developed b… 2017-12-06 00:00:00 https://www.bloomberg.com/news/articles/2017-12-06/the-computer-that-saved-a-vineyard CloudQuant Thoughts: We will drink to that! We may need to order a case or two for our Holiday party. You can find the vineyard at https://www.palmazvineyards.com/Microsoft doubles down on its ‘AI for Earth’ initiative, pledging $50M at Paris climate event
…Microsoft today pledged $50 million over five years for an initiative to use artificial intelligence to tackle the world’s most pressing environmental issues. Microsoft President and Chief Legal Officer Brad Smith will detail the company’s commitment to the program, known as AI for Earth, at the One Planet Summit in Paris later today. Started earlier this year, AI for Earth aims to put Microsoft’s vast AI resources in the hands of universities, non-governmental organizations and other groups to… 2017-12-11 11:01:28+00:00 https://www.geekwire.com/2017/microsoft-doubles-ai-earth-initiative-pledging-50m-paris-climate-event/ CloudQuant Thoughts: Private industry is taking initiative and leadership using AI to solve an issue that many are concerned with globally. Nice move Microsoft.What Does Your Cloud Data Look Like? QuantHouse Is Moving Historical Data On-demand To The Cloud
… also looking at the metadata space. Firms can now take their own trading information and identify better performance strategies for traders, or weed out problems with a particular strategy. Layer in artificial intelligence and machine learning tools and you can see the potential for firms and another phase of competition. QuantHouse moved to bolster its overall service offering with the acquisition of Victory Networks in September, giving it further reach in the high speed network space, especially for hedge funds and asset managers. Feligioni believes his firm is now well positioned for that client base which is … 2017-12-08 00:48:00+00:00 http://www.johnlothiannews.com/2017/12/cloud-data-look-like-quanthouse-moving-cloud/ CloudQuant Thoughts: Nice move QuantHouse. We like what you are doing. We also find that the cloud’s power for computing cycles provides a major opportunity for the industy.Nasa to hold major announcement after artificial intelligence makes major planet-hunting breakthrough
…ly relate to exoplanets – Earth-sized worlds that orbit around their own stars, and are our best hope of finding alien life. The space agency said that the discovery was made with the help of Google artificial intelligence, which is being used to analyse the data sent down by the telescope. By using machine learning provided by the tech giant, Nasa hopes that it can pick through the possible planets more quickly and hopefully find life-supporting planets sooner. Nasa said that four engineers and scientists would take part in the session. They include Paul Hertz, who leads Nasa’s astrophysics division, a senior Goo… 2017-12-11 08:53:56+00:00 http://www.independent.co.uk/life-style/gadgets-and-tech/news/nasa-announcement-today-latest-kepler-breakthrough-google-ai-artificial-intelligence-a8102966.html CloudQuant Thoughts: We already knew that machine learning is “Out of this world” but this just proves the point.Apple’s AI Chief Reveals Fresh Details About The Car Project
…researchers to share their work – primarily related to the car project – with the wider scientific community. Apple car project: It can detect objects hidden behind parked cars Speaking at the NIPS machine learning conference (via Wired), Apple’s AI director Ruslan Salakhutdinov provided some previously unpublicized details about the self-driving car technology. He offered a sneak peek into how Apple is using artificial intelligence and machine learning to detect pedestrians and make autonomous driving safer. More than 8,000 people attended the NIPS conference. He demonstrated a system that can identify ob… 2017-12-11 06:43:07-05:00 http://www.valuewalk.com/2017/12/apple-car-project-ruslan-salakhutdinov/#disqus_thread CloudQuant Thoughts: The trend is to be more open with technology. We see it in open source and crowdsourcing. Apple, with a very loyal community of users, always has a great opportunity to be a thought leader and not just an innovation leader. We like seeing them be more open.Quantitative Brokers Appoints Ralf Roth as CEO
…ch he will join. Roth will begin as CEO effective December 18th. “After a comprehensive search process, we are thrilled to appoint Ralf Roth as CEO. Ralf brings strong leadership and experience with machine learning and cloud computing that will help us scale and expand on the innovation that defines QB in the market,” said Christian Hauff, Co-Founder and outgoing CEO of Quantitative Brokers. Hauff will continue on as a member of QB’s Board and Executive Committee and will oversee the firm’s client and industry relationships. “Ralf is very well placed to succeed me in the role of CEO and I look forward to as… 2017-12-08 00:00:00 http://www.bobsguide.com/guide/news/2017/Dec/8/quantitative-brokers-appoints-ralf-roth-as-ceo/Google’s AI teaches itself chess in 4 hours, then convincingly defeats Stockfish
…There has just been a revolutionary development in the world of AI, and in the world of chess. Google’s Artificial Intelligence project, DeepMind explains they’re on a scientific mission to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how. A little over a year ago, DeepMind released AlphaGo, which sensationally defeated the world champion of the famously CPU unfriendly ancient Chinese game, GO. Now their AlphaZero program has kicked up a storm in … 2017-12-09 17:16:47+00:00 http://trove42.com/google-ai-teaches-itself-chess-defeats-stockfish/ CloudQuant Thoughts: Why does everyone want to play chess with AI and Machine Learning? We want to see some Machine Learning project team take on Settler Of Catan!CityBldr raises cash, prepares to expand to California with software that reveals hidden real estate value – GeekWire
…icer at Touchstone earlier this year. Initially, CityBldr was focused on residential properties but now has expanded its service to cover nearly all types of real estate. “What we’ve learned is our machine learning algorithm doesn’t care if its a house, or an apartment, or a gas station, or a vacant parcel of land, or a commercial building, or an office building … it doesn’t care at all,” Copley said. “It just sees that there’s opportunity in that land and it predicts the highest and best use of that land.” CityBldr is hoping to hire a team of about seven in Los Angeles and bring on an additional 15 to 20 … 2017-12-07 23:47:18+00:00 https://www.geekwire.com/2017/citybldr-raises-cash-prepares-expand-software-reveals-hidden-real-estate-value-california/ CloudQuant Thoughts: In Chicago, there is the unused old post office. The building is huge and spans a highway that most people in the western suburbs use. We wonder what CityBldr would recommend to the Chicago mayor about this building?The thoughts and opinions on this site do not represent investment recommendations by CloudQuant or our clients. Securities, charts, illustrations and other information contained herein are provided to assist crowd researchers in their efforts to develop algorithmic trading strategies for backtesting on CloudQuant.
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