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Atlas 4.0 Semantic AI Technology

Superior Insights at Scale

Introduction

What is Semantic AI

Semantic AI (SAI) is a new brand of AI algorithms which generates near-human insights. As opposed to the traditional machine learning algorithms SAI deals with the true underlying meaning of the data. In financial markets, this translates into digging into the meaning that a company/asset has in the world of finance. Instead of treating each company as a bunch of numeric metrics like return rate, earnings etc SAI analyzes what a company produces, what goes into each product, which company produces those materials (supply chain) and which company/entity buys the products (clients). SAI also considers entities such as interest rates, political developments, local and global events and investors who invest in the company. You probably have noticed that this kind of data encapsulates all the knowledge that we have about any given company. This is exactly what Assets 360° contains. In addition to this, we have designed properiotry Graph Neural Network (GNN) which extracts the meaning of this data and truly understands the essence of a given asset and its relation to the wider financial world. In the next section, we describe how such a GNN sees our data and how it reasons about it.

Tesla: A Case Study

Let's look at one specific company that has been garnering a lot of attention: Tesla Inc. The valuation has skyrocketed over the last year. But is the current valuation warranted? What is the right price for Tesla's shares? To answer this question, we need to map-out a reasoning process backed by data. Here is the kind of reasoning within reach of Atlas 4's AI technology:

Tesla's Businesses:

Tesla is chiefly an automaker in the EV industry. However, EVs are not the only product Tesla offers. The company is also involved in manufacturing EV-related products, such as rapid charging stations. It also manufactures lithium-ion batteries used, not only in EVs, but in the energy sector through Tesla Powerwalls used for energy storage.

Competition:

In terms of the automotive industry, Tesla's closest competitors are in the EU and China. While Volkswagen and BMW are present in the EV market, the real competition comes from three EV manufacturers in China: BYD, BAIC and SAIC. Together, these three companies surpass Tesla in terms of market share and expand into functional territories Tesla hasn't even entered (i.e. military vehicles and public transportation). Tesla is also active in EV charging technology. In this domain too, companies in China and Europe are posing an increasingly bigger risk to Tesla's market share.
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China and Europe have dominated the domain of fast charging standards through the CHAdeMO technology, Tesla is using its Supercharger standard. Tesla's standard though is very likely to be overpowered by Chineese and European ones as the latter is 3 times bigger in numbers across the globe (and we're not mentioning the CCS standard, another Chineese fornt-runner standard which is almost equally popular). Moreover, looking at the charging stations in France, Germany as well as other countries, we can clearly see that Tesla only has a tiny fraction of these stations operating. Finally, in terms of raw material, since EVs and Powerwalls are based on batteries, and these contribute to the price tag in a major way, Tesla is exposed to battery manufacturers and raw material mining companies. Acknowleding this, Tesla has been actively producing lithium-ion batteries but lagging behind CATL and LG Chemicals in terms of market share. But perhaps more importantly, it is leading BYD in this front which increases the likelihood that Tesla will have a much more powerful voice in the EV market too. Still, Tesla has a dependency on raw material such as Lithium, Cobalt and Graphite mainly mined in Australia, Chile and China (in order of capacity).

All these reasons explain a few things regarding Tesla's recent moves - it increased its presence in China and Australia, as well as developed its next Gigafactory in Asia. Our analysis also indicates that Tesla, while lagging behind some Chinese EV makers (some of which state-sponsored), is making strategic moves to tip the balance in its favour. When quantifying Tesla's value, all of the above reasoning and much more should be included in the estimation process.

The Value of Atlas 4's AI:

It is worth mentioning that this level of reasoning is almost impossible for current AI technologies. However, Atlas 4 has developed this ground-breaking technology. This means that we're able to provide such reasoning at scale for not just one asset, but all assets under our coverage. In other words, while our Assets 360° provides a comprehensive, inter-connected data for each asset (in much more depth and breadth than what we explained for Tesla above), Atlas 4.0's GNN-backed Semantic AI is designed to read this data to connect all the dots, make all the relevant comparisons and reasonings and provide metrics like value, exposure, synergy, merger likelihood and much more.

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Asta

Founder & CEO

April 20, 2020