To Compete With New Rivals, Chipmaker Nvidia Shares Its Secrets

Five years ago, Nvidia was best known as a maker of chips to power videogame graphics in PCs. Then researchers found its graphics chips were also good at powering deep learning, the software technique behind recent enthusiasm for artificial intelligence.

The discovery made Nvidia into the preferred seller of shovels for the AI gold rush that’s propelling dreams of self-driving cars, delivery drones and software that plays doctor. The company’s stock-market value has risen 10-fold in three years, to more than $ 100 billion.

That’s made Nvidia and the market it more-or-less stumbled into an attractive target. Longtime chip kingpin Intel and a stampede of startups are building and offering chips to power smart machines. Further competition comes from large tech companies designing their own AI chips. Google’s voice recognition and image search now run on in-house chips dubbed “tensor processing units,” while the face-unlock feature in Apple’s new iPhone is powered by a home-grown chip with a “neural engine”.

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Nvidia’s latest countermove is counterintuitive. This week the company released as open source the designs to a chip module it made to power deep learning in cars, robots, and smaller connected devices such as cameras. That module, the DLA for deep learning accelerator, is somewhat analogous to Apple’s neural engine. Nvidia plans to start shipping it next year in a chip built into a new version of its Drive PX computer for self-driving cars, which Toyota plans to use in its autonomous-vehicle program.

Why give away this valuable intellectual property for free? Deepu Talla, Nvidia’s vice president for autonomous machines, says he wants to help AI chips reach more markets than Nvidia can accommodate itself. While his unit works to put the DLA in cars, robots, and drones, he expects others to build chips that put it into diverse markets ranging from security cameras to kitchen gadgets to medical devices. “There are going to be hundreds of billions of internet of things devices in the future,” says Talla. “We cannot address all the markets out there.”

Source: S&P CapitalIQ

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One risk of helping other companies build new businesses is that they’ll start encroaching on your own. Talla says that doesn’t concern him because greater use of AI will mean more demand for Nvidia’s other hardware, such as the powerful graphic chips used to train deep learning software before it is deployed. “There’s no good deed that goes unpunished but net-net it’s a great thing because this will increase the adoption of AI,” says Talla. “We think we can rise higher.”

Mi Zhang, a professor at Michigan State University, calls open sourcing the DLA design a “very smart move.” He guesses that while researchers, startups, and even large companies will be tempted by Nvidia’s designs, they mostly won’t change them radically. That means they are likely to maintain compatibility with Nvidia’s software tools and other hardware, boosting the company’s influence.

Zhang says it makes sense that devices beyond cars and robots have much to gain from new forms of AI chip. He points to a recent project in his research group developing hearing aids that used learning algorithms to filter out noise. Deep-learning software was the best at smartly recognizing what to tune out, but the limitations of existing hearing aid-scale computer hardware made it too slow to be practical.

Creating a web of companies building on its chip designs would also help Nvidia undermine efforts by rivals to market AI chips and create their ecosystems around them. In a tweet this week, one Intel engineer called Nvidia’s open source tactic a “devastating blow” to startups working on deep learning chips.

It might also lead to new challenges for Intel. The company bought two such startups in the past year: Movidius, focused on image processing, and Mobileye, which makes chips and cameras for automated driving.

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3 Reasons To Buy Gilead

The Power Factors System is the backbone of my research service, The Data Driven Investor. It’s essentially a quantitative ranking system that selects stocks based on three powerful and time-proven return drivers: financial quality, valuation, and momentum.

Multiple academic studies have proven that companies exhibiting strong numbers in these three areas tend to beat the market in the long term, and my own backtesting work confirms that the Power Factors Systems can generate impressive performance over time.

The specific details behind the system are not particularly important, the main idea is using a combination of indicators and ratios to select companies with strong metrics in these main areas. Among others, the Power Factors System includes the following metrics:

  • Financial quality: the system looks for companies with superior profitability on sales, considering ratios such as gross profit margin and free cash flow margin. In addition, financial quality includes metrics based on return on capital, such as return on investment and return on assets.
  • Valuation: this covers classical valuation ratios like price to earnings, and price to free cash flow, among several other metrics based on similar concepts.
  • Momentum: the system picks companies that are outperforming expectations, and it also looks for stocks that are doing better than the broad market. In a nutshell, we want companies that are delivering performance numbers above Wall Street forecasts, and we also want the stock price to be reflecting such outperformance.

An equally-weighted portfolio comprised of the 50 best-ranking companies in the system produced an impressive annual return of 26.39% since 1999. By comparison, the S&P 500 produced a far more modest return of 3.77% per year over the same period.

In other words, a $ 100,000 position in the S&P 500 back in 1999 would currently be worth nearly $ 199,100, while the same amount of money invested in the Power Factors portfolio would be worth an exponentially larger sum of $ 7.8 million.

Data and chart are from Portfolio123, and the full list of companies in the system is available to subscribers in The Data Driven Investor.

The ranking system is based on a stock universe that excludes over-the-counter stocks in order to guarantee a minimum size and liquidity levels. Nevertheless, most stocks in the system are relatively smaller than those in the S&P 500, and in many cases far more volatile.

Interestingly, Gilead (GILD) is a noteworthy exception. The company has a market capitalization value of more than $ 109.6 billion, and it ranks remarkably well across the three dimensions in the Power Factors System. These particularities make of Gilead a particularly intriguing name among the stocks selected by the quantitative model.

Case Study: Gilead

Gilead is a leading player in the biotech space. The company is focused on life-threatening infectious diseases, with a big presence in treatments for HIV, hepatitis B, and hepatitis C. Gilead has made a series of acquisitions to expand its portfolio in cardiovascular diseases and Cancer over the past several years. More recently, the company made a big move with the acquisition of Kite Pharma (KITE) for $ 11.9 billion in cash. This deal could provide a big boost to Gilead in cell therapy and oncology treatments.

The business is under pressure due to lower sales and increasing competition in Hepatitis C (HVC) products.

On the other hand, Gilead has a promising pipeline of new developments across different areas, and this should drive increased revenue growth over the years ahead.

Importantly, the company has an impressive track record of financial performance over the long term, and profitability levels are considerably above-average. The following table compares key financial metrics for Gilead vs. other big biotech companies, such as Amgen (OTC:AMGM), Celgene (CELG), and Biogen (IBB).

5 Year Sales Growth.

Return on Assets (ROA)

Return on Investment (ROI)

Operating Margin

Net Margin

Gilead

29.4%

21.1%

31%

57.8%

42.9%

Amgem

8.1%

10.4%

13%

44.7%

35.5%

Celgene

18.3%

9.1%

11.7%

27.6%

21.3%

Biogen

17.8%

15%

21%

38.7%

28.1%

The numbers are quite clear, Gilead ranks above the competition across all of the five indicators: sales growth over the past five years, return on assets, return on investment, operating margin, and net margin.

Financial performance over the years ahead will depend on variables such as demand for Gilead’s new products, and this is always a source of uncertainty. Nevertheless, the company’s track-record and current performance are a positive reflection on its management team and its ability to deliver attractive returns for shareholders.

In terms of valuation, Gilead stock is fairly conveniently priced, if not downright undervalued. The stock trades at a price to earnings ratio around 9.15 times earnings over the past year. This is a huge discount versus the average company in the S&P 500, which trades at a price to earnings ratio around 21.5.

Looking at valuation ratios in comparison to industry peers, Gilead also looks quite cheap in terms of price to earnings, forward price to earnings, price to free cash flow, and price to sales.

P/E

Forward P/E

P/FCF

P/S

Gilead

9.1

11.2

10.1

3.85

Amgem

16.9

14.5

18.7

5.9

Celgene

44.7

16.1

26.8

9.2

Biogen

29.8

13.7

18.21

5.7

Offering a similar perspective, the following chart shows how Gilead’s valuation has evolved over the past several years, and current entry price looks quite compelling by historical standards in terms of price to earnings, price to free cash flow, and enterprise value to EBITDA.

ChartGILD PE Ratio (ttm) data by YCharts

The bottom line is that Gilead stock is substantially cheap, be it in comparison to the broad market, when compared to industry peers, or by the company’s own historical standards.

Momentum is favoring the bulls. Both revenue and earnings came in above Wall Street expectations last quarter, and analysts are adjusting their earnings forecasts to the upside. The average earnings estimate for Gilead in 2017 was $ 8.35 per share 90 days ago, and it has steadily increased towards $ 8.78 currently.

Stock prices don’t just reflect fundamentals, expectations about those fundamentals are tremendously important. When expectations are on the rise, this generally means that stock prices are rising too. On the back of increasing earnings forecasts, Gilead stock has substantially outperformed the S&P 500 index over the past several months.

ChartGILD data by YCharts

Past performance does not guarantee future returns. However, profitability metrics, valuation, and momentum are all positive forces for investors in Gilead on a forward-looking basis.

Disclosure: I am/we are long GILD.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

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