Backgrounder:
Artificial intelligence (AI) continues both to astound and confound. AI finds patterns in data and then uses a technique called “reinforcement learning from human feedback.” Humans help train and fine-tune large language models (LLMs). Some humans, like “ethics & compliance” folks, have a heavier hand than others in tuning models to their liking.
Generative Artificial Intelligence (generative AI) is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. AI technologies attempt to mimic human intelligence in nontraditional computing tasks like image recognition, natural language processing (NLP), and translation. Generative AI is the next step in artificial intelligence. You can train it to learn human language, programming languages, art, chemistry, biology, or any complex subject matter. It reuses training data to solve new problems. For example, it can learn English vocabulary and create a poem from the words it processes. Your organization can use generative AI for various purposes, like chatbots, media creation, and product development and design.
Review of Leading AI Company Products and Services:
1. AI poster child Nvidia’s (NVDA) market cap is about $2.3 trillion, due mainly to momentum-obsessed investors who have driven up the stock price. Nvidia currently enjoys 75% gross profit margins and has an estimated 80% share of the Graphic Processing Unit (GPU) chip market. Microsoft and Facebook are reportedly Nvidia‘s biggest customers, buying its GPUs last year in a frenzy.
Nvidia CEO Jensen Huang talks of computing going from retrieval to generative, which investors believe will require a long-run overhaul of data centers to handle AI. All true, but a similar premise about an overhaul also was true for Cisco in 1999.
During the dot-com explosion in the late 1990s, investors believed a long-run rebuild of telecom infrastructure was imminent to build out the internet which was said to be doubling in traffic every few months. The thinking at that time was that the whole internet would run on Cisco routers at 50% gross margins. Cisco’s valuation at its peak of the “Dot.com” mania was at 33x sales. CSCO investors lost 85% of their money when the stock price troughed in October 2002. Over the next 16 years, as investors waited to break even, the company grew revenues by 172% and earnings per share by a staggering 681%. Over the last 24 years, CSCO buy and hold investors earned only 0.67% per year!
2. Microsoft is now a cloud computing/data-center company, more utility than innovator. Microsoft invested $13 billion in OpenAI for just under 50% of the company to help develop and roll out ChatGPT. But much of that was funny money — investment not in cash but in credits for Microsoft‘s Azure data centers. Microsoft leveraged those investments into super powering its own search engine, Bing, with generative AI which is now called “Copilot.” Microsoft spends a tremendous amount of money on Nvidia H100 processors to speed up its AI calculations. It also has designed its own AI chips.
3. Amazon masquerades as an online retailer, but is actually the world’s largest cloud computing/data-center company. The company offers several generative AI products and services which include:
Amazon CodeWhisperer, an AI-powered coding companion.
Amazon Bedrock, a fully managed service that makes foundational models (FMs) from AI21 Labs, Anthropic, and Stability AI, along with Amazon’s own family of FMs, Amazon Titan, accessible via an API.
A generative AI tool for sellers to help them generate copy for product titles and listings.
Generative AI capabilities that simplify how Amazon sellers create more thorough and captivating product descriptions, titles, and listing details.
Amazon CEO Jassy recently said the the company’s generative AI services have the potential to generate tens of billions of dollars over the next few years. CFO Brian Olsavsky told analysts that interest in Amazon Web Services’ (AWS) generative AI products, such as Amazon Q and AI chatbot for businesses, had accelerated during the quarter. In September 2023, Amazon said it plans to invest up to $4 billion in startup chatbot-maker Anthropic to take on its AI based cloud rivals (i.e. Microsoft and Google). Its security teams are currently using generative AI to increase productivity
4. Google, with 190,000 employees, controls 90% of search. Google‘s recent launch of its new Gemini AI tools was a disaster, producing images of the U.S. Founding Fathers and Nazi soldiers as people of color. When asked if Elon Musk or Adolf Hitler had a more negative effect on society, Gemini responded that it was “difficult to say.” Google pulled the product over “inaccuracies.” Yet Google is still promoting its AI product: “Gemini, a multimodal model from Google DeepMind, is capable of understanding virtually any input, combining different types of information, and generating almost any output.”
5. Facebook/Meta controls social media but has lost $42 billion investing in the still-nascent metaverse. Meta is rolling out three AI features for advertisers: background generation, image cropping and copy variation. Meta also unveiled a generative AI system called Make-A-Scene that allows artists to create scenes from text prompts . Meta’s CTO Andrew Bosworth said the company aims to use generative AI to help companies reach different audiences with tailored ads.
Conclusions:
Voracious demand has outpaced production and spurred competitors to develop rival chips. The ability to secure GPUs governs how quickly companies can develop new artificial-intelligence systems. Tech CEOs are under pressure to invest in AI, or risk investors thinking their company is falling behind the competition.
As we noted in a recent IEEE Techblog post, researchers in South Korea have developed the world’s first artificial intelligence (AI) semiconductor chip that operates at ultra-high speeds with minimal power consumption for processing large language models (LLMs), based on principles that mimic the structure and function of the human brain. The research team was from the Korea Advanced Institute of Science and Technology.
While it’s impossible to predict how fast additional fabricating capacity comes on line, there will surely be many more AI chips from cloud giants and merchant semiconductor companies. Fat profit margins Nvidia is now enjoying will attract many competitors.
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References:
https://www.zdnet.com/article/how-to-use-the-new-bing-and-how-its-different-from-chatgpt/
https://cloud.google.com/ai/generative-ai
https://aws.amazon.com/what-is/generative-ai/
https://www.wsj.com/articles/amazon-is-going-super-aggressive-on-generative-ai-7681587f
Meta wants to use generative AI to create ads
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