Major Tech Shifts Drive Investments
Major Tech Shifts Drive Investments
(repost, original here)
At Tsingyuan Ventures, we invest in early stage technology startups that can potentially generate big returns. These types of startups typically happen alongside major technological shifts in the world. The shifts are necessary as they create windows of opportunity for startups to challenge/disrupt much larger incumbents of the respective sectors. In this post, I’d like to discuss the following five major technology shifts in the software category.
1. Enterprise Software Shifts to Public Cloud
The major replacement cycle in B2B software infrastructure happens around tech platform shifts. In recent years, one such shift is the shift to the public cloud. In the US, the public cloud market is dominated by Amazon AWS, Microsoft Azure, and Alphabet’s Google Cloud. These three are also top global players with Alibaba being the biggest non-US player.
As public cloud spend continues to rise significantly (this IDC report forecast $160B globally this year with 22% annual growth rate), a good investment in this sector will enjoy a big boost from the sector growth. While much of the cloud-based software re-investment has already been baked in, I believe that — in a hybrid-cloud environment — enterprise security, DevOps, data management and optimization are a few areas that still have significant opportunities.
2. Device Intelligence: Shift to Edge Computing
Contrary to enterprise software’s shift to cloud, device intelligence (or IoT: internet of things) is shifting to the edge. As devices (eg., cameras and sensors) become more capable in collecting large amounts of data, networking pathways and centralized processing servers start to become bottlenecks. So we need to bring computation to the data. The investments will be around low power, low cost edge computing processors and new algorithms.
3. AI: Deep Learning in NLP and Computer Vision
Deep learning neural networks have made significant progress in recent years, especially in the area of speech/language understanding, image recognition and video analysis. While the Alexa platform has quickly dominated the consumer market, I’m more excited about the enterprise world of external customer service, pre-sales support, and internal information retrieval and support applications. “Alexa for enterprise” may sound cliche but is fairly accurate here.
Deep learnings improvement on computer vision is even more visible, pun intended. When combined with significantly better and cheaper camera modules, computer vision has finally crossed over the threshold of human vision capabilities. I’m particularly excited about such diverse use cases as autonomous driving, security surveillance, medical imaging and crowd data collection in traffic/retail/office.
4. Computing Shifts from CPU to GPU
Moore’s Law states that CPU transistor counts double every 2 years. While it is still largely true, the expected performance increase has significantly slowed. Because power consumption and therefore clock speed has become the bottleneck, computing capacity has shifted to multi-core (low 10s), many-core (high 10s) or even GPU level (up to 1000s of cores).
This creates a number of opportunities:
- Software architectures need significant change to adapt to new computing;
- Processor architectures become more fragmented and fluid.
- Data storage and data pathways become the bottleneck in computing.
I believe major investment opportunities exist in GPU optimized software tools, high-performance data storage systems, and application dependent massively parallel computing systems.
5. Shift to EV and Autonomous Driving
Autonomous driving is loosely dependent on automotive electrification due to the extra sensors and computing power required. Cars in general will also be driven a much higher percentage of time (driven by both autonomy and car sharing). This has implications for power consumption and energy storage. Automobile electrification is already happening at a fast pace in China. I believe autonomous driving will be adopted at scale in China first as well.
This is a mega trend in terms of dollars as well as the number of industry sectors it disrupts. I believe there are substantial investment opportunities in automotive electronics and software, autonomous driving, energy storage, and smart cities as traffic patterns and real estate needs shift.
In the next few posts, I’ll dive into each of these five areas in more detail and give more examples. In the meantime, you can read my partner Eric’s posts about Tsingyuan Ventures’ investment philosophy with regard to cross-border deals and cross-disciplinary deals.
