Richard Windsor
5 December 2017

Google - Brain game pt. II

Google remains out front in AI but Baidu most interesting.

The first results from Google’s AutoML project are beginning to surface and are implying once again that machines may end up being better coders than humans.
AutoML was announced at Google i/o in May 2017 and failed to attract much attention mainly because most commentators did not grasp the significance of the concept. AutoML is neural network that is capable selecting the best from a large group neural networks that are all being trained for a specific task. This is potentially a hugely important development as it marks a step forward in the quest to enable the machines to build their own AI models.

Building models today is still a massively time and processor intensive task which is mostly done manually and is very expensive. If machines can build and train their own models, a whole new range of possibilities is opened-up in terms of speed of development as well as the scope tasks that AI can be asked to perform.  In the subsequent months since launch, AutoML has been used to build and manage a computer vision algorithm called NASNet. AutoML has implemented reinforcement learning on NASNet to improve its ability to recognise objects in video streams in real time. When this was tested against industry standards to compare it against other systems, NASNet outperformed every other system available and was marginally better than the best of the rest. This is significant because it is another example of when humans are absent from the training process, the algorithm demonstrates better performance compared to those trained by humans.

Big challenges in AI include the ability to train AIs using much less data than today, the creation of an AI that can take what it has learned from one task and apply it to another and the creation of AI that can build its own models rather than relying on humans to do it. When we look at the progress that has been made over the last year in AI, we think that Google has continued to distance itself from its competition.
Facebook had made some improvements around computer vision, but its overall AI remains so weak that it is being forced to hire 10,000 more humans because its machines are not up to the task. Consequently, we continue to see Google out front followed by Baidu and Yandex with Microsoft, Apple and Amazon making up the middle ground. Facebook remains at the back of the pack and its financial performance next year is going to be hit by its inability to harness machine power. For those looking to invest in AI excellence, Baidu is the place to look as its search business and valuation has been hard hit by Chinese regulation but is now starting to recover. Baidu represents one of the cheapest ways to invest in AI available.

Disclaimer - Past performance is no guarantee of future results. Inherent in any investment is the potential for loss. This material is being provided for informational purposes only and nothing herein constitutes investment, legal, accounting or tax advice, or a recommendation to buy, sell or hold a security. This document may contain materials from third parties, which are supplied by companies that are not affiliated with Edison Investment Research. Edison Investment Research has not been involved in the preparation, adoption or editing of such third-party materials and does not explicitly or implicitly endorse or approve such content. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. It should not be assumed that any investments in securities, companies, sectors or markets identified and described were or will be profitable. All information is current as of the date of publication and is subject to change without notice. While based on sources believed reliable, we do not represent this material as accurate or complete. Any views or opinions expressed may not reflect those of the firm as a whole. Edison Investment Research does not engage in investment banking, market making or asset management activities of any securities. The material has not been prepared in accordance with the legal requirements designed to promote the independence or objectivity of investment research.