Machine learning is an artificial intelligence (AI) technology which allows machines to learn by using algorithms to interpret data from connected ‘things’ to predict outcomes and learn from successes and failures.
There are many other AI technologies - from image recognition to natural language processing, gesture control, context awareness and predictive APIs - but machine learning is where most of the investment community’s funding has flowed in recent years. It is also the technology most likely to allow machines to ultimately surpass the intelligence levels of humans. Many companies, like Alphabet, have already become ‘AI-first’ companies, with machine learning at their core. At the same time, many ML techniques are getting commoditised by being open sourced and pre-packaged into developer toolkits that anyone can use. This means that the time taken for Alibaba and Baidu to catch-up with Alphabet and Microsoft will be minimal.
Inside this report, we look at the key players impacted by this theme, drilling down into the value chain and identifying winners and losers.
- This report is part of the ecosystem of thematic investment research reports, supported by the “thematic engine”.
- About the Thematic Research Ecosystem
- The author has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, the author’s thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, the author tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores. The algorithms in the author’s “thematic engine” help to clearly identify the winners and losers within the TMT sector. The 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. The thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Single Theme report, offering in-depth research into a specific theme. It identifies winners and losers based on technology leadership, market position and other factors.
- The thematic investment research product, supported by the thematic engine, is aimed at senior (C-Suite) executives in the corporate world as well as institutional investors.
- Corporations: Helps CEOs in all industries understand the disruptive threats to their competitive landscape
- Investors: Helps fund managers focus their time on the most interesting investment opportunities in global TMT.
- The unique differentiator, compared to all rival thematic research houses, is that the thematic engine has a proven track record of predicting winners and losers.
Ten key AI technologies
History of machine learning
How does deep learning work?
Use case trends
Optimised networking equipment
High end processors
Master data management
Developer tools (APIs and SDKs)
Software with embedded AI
AI and ML likely to become widespread because too much is open sourced
AI and ML are transforming the semiconductors market
Privately held companies
APPENDIX: “THEMATIC” RESEARCH METHODOLOGY
- AAC Technologies
- HP Enterprise
- Nuance Communications
- Samsung Electronics
- Silicon Labs
- SK Hynix
- Tata Consultancy Services
- TE Connectivity
- Texas Instruments