- Last week, JP Morgan released “Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing”, a report which said “over the past year, the exponential increase of the amount and types of data available to investors prompted some to completely change their business strategy and adopt a ‘Big Data’ investment framework. Other investors may be unsure on how to assess the relevance of Big Data and Machine Learning, how much to invest in it, and many are still paralyzed in the face of what is also called the ‘Fourth Industrial Revolution … As more investors adopt alternative datasets, the market will start reacting faster and will increasingly anticipate traditional or ‘old’ data sources (e.g. quarterly corporate earnings, low frequency macroeconomic data, etc.). This gives an edge to quant managers and those willing to adopt and learn about new datasets and methods. … Regardless of the timeline and shape of the eventual investment landscape, we believe that analysts, portfolio managers, traders and CIOs will eventually have to become familiar with Big Data and Machine Learning approaches to investing. This applies to both fundamental and quantitative investors, and is true across asset classes.”
- Also, the non-profit AI research group, OpenAI, said in the note Robots that Learn “We’ve created a robotics system, trained entirely in simulation and deployed on a physical robot, which can learn a new task after seeing it done once. Now, we’ve developed and deployed a new algorithm, one-shot imitation learning, allowing a human to communicate how to do a new task by performing it in [virtual reality]. Given a single demonstration, the robot is able to solve the same task from an arbitrary starting configuration.
- Note: OpenAI’s backers include include Sam Altman, Greg Brockman, Elon Musk, Reid Hoffman, Jessica Livingston, Peter Thiel, Amazon Web Services, Infosys, YC Research and Microsoft.
- Finally, during its developer conference, Google announced that “Researchers require enormous computational resources to train the machine learning (ML) models that have delivered recent breakthroughs in medical imaging, neural machine translation, game playing, and many other domains. We believe that significantly larger amounts of computation will make it possible for researchers to invent new types of ML models that will be even more accurate and useful. To accelerate the pace of open machine-learning research, we are introducing the TensorFlow Research Cloud ... to support a broad range of computationally-intensive research projects that might not be possible otherwise."
- Regarding JP Morgan’s comments – As technology continues to reshape the financial services industry, it is worth revisiting a famous quote by Walter Wriston (CEO of Citibank / Citicorp from 1967 to 1984): “Information about money has become almost as important as money itself”.
- Regarding Robots that Learn – this example of the integration of AI, virtual reality and robotics illustrates the future direction of product prototyping and design.
- Regarding Google’s TensorFlow cloud – the battle for mind-share among software developers and researchers will require significant investments by firms including Amazon, Microsoft, F
acebook, Apple and IBM.