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Remark Holdings…Notes From My Meeting With The CEO

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I had the pleasure of meeting Shing Tao, the CEO of Remark Holdings (NASDAQ:MARK), on Monday night. He had just flown into San Francisco from Beijing and I was meant to be his first meeting before dinner and some shut eye; he had a big Tuesday in front of him with Roth Capital (whose analyst loves MARK, although they haven't been their bankers) taking him on a Non-Deal Roadshow and introducing him to several institutional investors. Remark has been very hot lately, jumping almost 200% in value since the company reported Q3 earnings in mid-November. The move came on the back of 2018 revenue guidance for their Artificial Intelligence operating subsidiary, KanKan. They guided to $30M in KanKan AI revenues for next year, which would be a 500% increase over 2017.


How can investors use machine learning to pick the right startups?

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When considering a startup, especially an early-stage startup, investors want to conduct as much due diligence as possible. What little data they can gather is scattered all over different sources including Crunchbase, LinkedIn, Pitchbooks, company websites, etc. Consolidating this data takes a great amount of time and effort. Furthermore, the data sets can be incomplete or biased depending on the search queries -- imagine overlooking a keyword. To make the due diligence process fairer and less cumbersome for investors, various platforms are using machine learning (ML) to pull together information about startups from all available resources to help investors assess companies and investment opportunities. But where machine learning really shines is in the interplay of data-driven insights that are qualified by human intuition and personal experience.


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Although the average consumer may not be familiar with the concept of machine learning, it's already a big part of our daily lives. Tom Schlebusch, the co-founder and chief executive of NMRQL Research, a local fintech player offering South Africa's first machine-learning-powered unit trust fund, says machine learning has a big role to play in how we invest our money. Amid the explosion of data and the exponential advancement of technology, investors are beginning to realise the benefits of machine learning in investment management. Schlebusch says that, when Amazon or Netflix makes recommendations that appeal to us, it's because machine learning was used to analyse our behaviour. "All social media platforms use machine learning to provide personalised feedback based on behaviour patterns and relationships with other users.


Deep learning and big data: Wall Street and the new data paradigm

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Wall Street is big business, and it is about to become even bigger with the rise of big data. It is every investor's dream to have prior knowledge of the direction of the market before it happens, which is why financial investment firms are driven to mine for data rather than for gold in the information economy. Traditionally, investors have based their decisions on fundamentals, intuition, and analysis drawn from traditional data sources, such as quarterly earnings reports, financial statement filings to the U.S. Securities and Exchange Commission (SEC), historical market data, institutional research reports and sometimes the so-called "expert networks." The new data-driven paradigm, fueled by new alternative data sources, high performance computing and predictive analytics, offers a more robust framework to generate data-driven investment theses. Data – from satellite images of areas of interest, automated drones, people-counting sensors, container ships' positions, credit card transactional data, jobs and layoffs reports, cell phones, social media, news articles, tweets, online search queries – is now the most valuable commodity for Wall Street.


The advisor's guide to AI

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Once the domain of large institutions with deep pockets, artificial intelligence is being adopted by RIAs and fee-based advisors to enhance the human connection with clients -- and gain an edge over the competition -- by transforming every aspect of the customer experience, from the front-end to the back office. Advisors say customer experience is a leading competitive advantage according to the latest Advisor Authority 360-degree Special Report on the DNA of the advisor-investor relationship. Ninety-four percent of RIAs and fee-based advisors say that the customer experience is important to their value proposition because it improves client retention. Both advisors and investors agree that building a personal one-on-one relationship is among the top factors to ensure success. And artificial intelligence is key.


Investors are losing out on billions because tech stocks don't pay dividends

USATODAY

If Alphabet, Amazon and Facebook (along with Berkshire Hathaway) paid shareholder dividends at the 2.37% average yield of other S&P 500 companies that do so, it would shake out another $32.2 billion for investors, according to Howard Silverblatt, senior index analyst at S&P Dow Jones Indices. How to choose a smart speaker More: Here's one way Google envisions search changing for you But don't expect these tech companies to pay a dividend anytime soon. "During the 1990s, tech didn't typically pay dividends and they drove the stock market back then," said Kim Forrest, senior equity analyst at Fort Pitt Capital. The S&P tech sector had a dividend yield of 1.36% during the third quarter, the lowest of the 11 sectors and well below the overall S&P 500 of 1.97%, according to Silverblatt.


Artificial Intelligence, Machine Learning, and Deep Learning: A Primer for Investors @themotleyfool #stocks $GOOGL, $NVDA, $GOOG

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Instead of preprogramming software to complete a specific task, as narrow AI does, machine learning uses algorithms that allow a computer to learn from the vast amounts of data it receives so it can complete a task on its own. International Business Machines uses deep learning powered by NVIDIA's graphics processing units (GPUs) to comb through medical images to find cancer cells. The company makes the graphics processors that are integral in AI, machine learning, and deep learning, and lots of companies already look to NVIDIA's hardware to make their AI software a reality. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), Amazon, Facebook, and Nvidia.



Finally, Amazon Artificial Intelligence Got Wings to Fly High

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This type of personal AI had been introduced previously in the mega-hit movie "Iron Man' with the AI system called "Jarvis." Right now most drones use a joypad/joystick style controls to operate the drone, by contrast, this company is developing its drone (called "ORCA") to utilize open networking/the Internet. Contributing to the crowdfund campaign will allow the development team to fully develop this model so that more people can benefit from AI based drones. In fact, it will allow for AI technology provided by Amazon AWS to be used by drones.


NVIDIA's Processors May Soon Power Wal-Mart's Deep Learning Push @themotleyfool #stocks $WMT, $NVDA

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Recently, analyst Trip Chowdhry of Global Equities Research wrote in an investor note that Wal-Mart Stores (NYSE:WMT) will ramp up its focus on deep neural networks for its OneOps cloud business and that the retailer will tap NVIDIA's (NASDAQ:NVDA) graphics processing units (GPUs) to make this happen. Deep neural networks, and the broader deep learning segment, are part of a growing artificial intelligence market. Additionally, NVIDIA said in its second-quarter fiscal 2018 report that it forged new partnerships with Microsoft, Google, Tencent, IBM, Baidu, and Facebook to help them bring new deep learning and artificial intelligence services online. Aside from NVIDIA's deep-learning total addressable market, adding more of these customers is important, because the company's data center revenue segment (which includes GPU sales for deep-learning technologies) is becoming a larger part of the business.