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    Unveiling 2024 AI Investment Trends: Following the Trillion-Dollar Money Trail

    Investors have poured $330 billion into 26,000+ AI and machine-learning start-ups over the past three years, a 66% increase from the previous three years.

    Why it matters

    Trend spotting is both an art and a science.

    In the high-velocity world of AI, it is hard to discover what is a fad versus what is an emerging and long-lasting trend. Following the money trail makes identifying the major AI trends a little easier.

    Picking winners and losers and getting your timing right as an investor is the difference between success and failure. 

    AI is the fastest emerging digital technology I have observed since starting in the technology sector 40 years ago.

    It is a generational revolution. It may even be as significant as the era of the “Renaissance”, which was accelerated by the invention of the printing press, and also the era of the “Enlightenment.”

    The opportunities are immense, as we are just at the start of the AI gold rush.

    Following the money trail can help identify where human investors think they will win. Which sectors, companies, and startups will challenge the big four? Otherwise known as FANG: Facebook, Amazon, Netflix, and Google.

    We also need to consider another four companies: Microsoft, Nvidia, Apple, and Tesla. 

    The big picture

    If you get too close to AI, it will overwhelm you with noise and complexity. So, to try and make sense of artificial intelligence, we need to stand back and get a sense of the big picture.

    This includes the 3 core pillars of AI and the AI ecosystem.

    The 3 pillars of AI

    There are 3 pillars in the AI ecosystem that need to be considered when choosing where to play (as an entrepreneur) and where to invest (as an investor). 

    1. Software – The general ecosystem of ChatGPT and its downstream niche applications and software built around the ChatGPT universe.
    2. Hardware – The data centers and the computer processors that bring the grunt and muscle to training and interrogating the AI brain.  
    3. Data -The data and information needed to train the AI LLMs (Large Language Models), both the web and the new artificial data that builds the generative AI machine.

    The AI ecosystem

    There is also an ecosystem in play for the software, which is the intelligence that is fed by the data-training AI. It showcases an ecosystem of different platforms and apps targeted at various segments. 

    Sequoia Capital (a venture capital company) breaks up the Generative AI Market into 4 segments.  

    1. Consumers –  Apps and platforms for the average consumer to use. Examples include TikTok and Spotify
    2. Prosumers – This is an individual who both consumes and produces. Examples include ChatGPT and Gemini
    3. Horizontal Enterprises – This space is where AI is applied generally. Examples include Adobe, Hubspot and Salesforce
    4. Vertical Enterprises – This is where specific industries scale and produce solutions for their particular niche. Examples include Ambience and Memora Health 
    Unveiling 2024 AI Investment Trends: Following the Trillion-Dollar Money Trail
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    By the numbers

    To try and make sense of this I have broken up the AI technology arms race into two camps.

    The large multinationals (valued in the trillions) and the nimble (but capital starved) startups fighting for scraps.

    Some of these startups will break through and become trillion-dollar companies.

    But the trillion-dollar question? Which ones? 

    Investing in training AI and providing the processing power is something that only the companies that are worth $1-3 trillion can fund.

    The startups are up against these global corporations that have more revenue and market value than the GDP of many countries.  

    Eight of these global companies are worth over 1 trillion dollars.

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    If you compare the market value of these companies to the  GDP of countries you’ll quickly understand why these companies have so much power. 

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    These trillion-dollar companies would rank in the following order if they were a country.

    • Apple would come in at #8 between the UK and France
    • Microsoft would come in at #9 between France and Italy
    • Then Saudi Aramco would be placed at #10 before Italy
    • Alphabet would be ranked at #12 after Russia and before South Korea
    • Amazon comes in at #17, just behind Indonesia

    The market value and the global reach that is transnational of these trillion-dollar companies has never happened before. 

    And it has large implications for their influence on culture and investments.   

    AI investments 

    According to this recent article in the New York Times, industry veterans have been surprised by the scale and capital needed to grow an AI company.

    The startups and upstarts

    Any technology revolution ends up being a battle between nimble and innovative and large and slow. But sometimes, they team up and get the best of both worlds.

    One of those is the partnership between OpenAI (ChatGPT) and Microsoft.

    • Inflection AI – Raised $1.5 billion but made no money (was acquired by Microsoft)
    • OpenAI – Backed by Microsoft ($13 billion) and is set to hit $2 billion in revenue this year. 
    • Anthropic – Raised $7 billion backed by Google and Amazon. Spending $2 billion a year with revenue of $200 million. But despite it being independent, it is backed by two of the trillion-dollar companies. 

    The big boys

    We have seen the rise of large multinational companies with deep pockets and wealth which allows them to play a big game. 

    Let’s take a closer look at where they are spending their money in the world of AI 

    1. Microsoft

    Microsoft has invested $13 billion in OpenAI and its poster child, ChatGPT.

    The bet looks like it’s paying off as currently they are the most valuable company in the world at over $3 trillion dollars. 

    On top of that they have just bought Inflexion for hundreds of millions of dollars and brought their team over to the new Microsoft “AI” division.

    Mustafa Suleyman (who created the Inflexion startup and was a co-founder of DeepMind) now heads the ongoing focus of Mirosoft on generative AI. 

    So where are they spending their money on AI? 

    2. Google (also known as Alphabet) 

    One of the key AI innovators has been Google. But its fear of destroying its own business model made it an AI malingerer. Google delayed because it wasn’t “perfect.” 

    It is now playing catch up.

    So where are they spending their money on AI? 

    3. Facebook (also known as Meta)

    Facebook has been spending its hard earned money on the pipe dream of virtual reality for many years and has now realized that it was following the wrong trend. 

    Wealth doesn’t mean wisdom. 

    It is now following the pied piper into the gold rush of “AI” 

    So where are they spending their money on AI? 

    4. Apple

    Apple is playing catch up. This is no surprise as a company that was the most valuable in the world didn’t see the need to invest in AI. 

    Now it has realized that current success doesn’t mean future success and the scramble to catch up is “go.”

    So where are they spending their money on AI? 

    Apple being pants down on AI is revealed in this one piece of data. How much they are spending and compare that to the other large platforms. 

    5. Nvidia

    These chip guys were originally known for being the masters of creating computer chips (sometimes called computer processors) for online computer games. It just so happens that these chips are perfect for AI data processing and LLM data training. 

    So all the big tech companies now want their computer processors.  

    Their market value has exploded and today they are a trillion dollar company. Nvidia is up almost 1800% in just 5 years.

    It is expected to report a revenue increase of 231% year on year for the last quarter with revenue of $20 billion. 

    So where are they spending their money on AI? 

    Nivida is investing in its research and services and has spent a lot of 2023 acquiring AI companies.

    The company’s investment strategy centers around companies that use its technology and products.

    In 2024 Nvidia is valued at over $2 billion and is the third most valuable company in the world behind Microsoft and Apple.

    6. Amazon

    Amazon has an ocean of data and has been using AI to help their customers choose their next book, select a video on Amazon Prime streaming, suggest a new product to buy from the Amazon store and much more.

    It is personalization at scale. Humans are crap at this but this is an AI superpower!

    So where are they spending their money on AI? 

    One of their biggest money earners are its data centers. The Amazon Web Services (AWS) division is a world leader with annual revenues of over $90 billion per annum

    AI needs a lot of processing horsepower and that means a lot of data centers.  

    Investment profile

    • Amazon has just invested $2.75 billion into Anthropic which is an AI startup that competes directly with ChatGPT with its Claude 3 Chat app 
    • They have also said they are committed to spending $150 billion in the next 15 years on data centers to support AI

    What are the 3 big AI trends?

    In the gold rush era the gold miners were chasing the big nuggets and big wins. 

    The reality? Not many made it big.  

    But the ones that made the big money were those that sold the shovels to the gold miners. These companies provided the tools and technology to unearth the gold and mine the gold seams.

    In the AI gold rush this includes tools like data centers, processors and software.

    #1: Data centers

    Amazon is reportedly going to spend $150 billion in the next 15 years to build data centers needed for the AI boom. Microsoft and OpenAI are planning a $100 billion data-center project

    #2: AI computer processors

    If you just look at Nvidia’s annual revenue from Jan 31, 2023 to Jan 31, 2024 the $60 billion of computer chip sales gives you an indication of the investment pouring into AI computer processors. That was a 260% increase in sales from the year before.

    The high cost of each processor, sometimes $10,000 each, means that companies like Meta, Microsoft, Samsung and  Google are now designing and developing their own processors. 

    #3: Software and apps (general and niche)

    Microsoft has invested $13 billion in ChatGPT software training and that includes the investment funding the processing of the AI development and the prompts and questions on ChatGPT in Microsoft’s data centers.

    Investing in AI

    You can try choosing a winner or you can invest in the general market segment. 

    Picking investment winners from an ocean of 26,000 startups is a dart board project. 

    It’s a crap shoot that may end in tears or you may get lucky. But if you are a betting person then you may enjoy the opportunity to lose your hard-earned savings.

    The best way to invest in AI is through an ETF fund with a range of AI investments which are usually passive. 

    According to USNews here are six best AI ETFs:

    And here are the top 10 AI ETFs by one year performance (according to Nerdwallet).

    What companies and which sectors are they investing in?

    Without going too deep, let’s look at one of the top 10 funds and where they are putting their investments.

    The Global X Artificial Intelligence & Technology ETF has achieved a 35.22% return in one year.  

    The companies

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    The industry sectors

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    The bottom line

    The current AI investment trends start to come into sharper focus when you see where the money is going.

    AI only came into the general public consciousness in November 2022 when it started to be democratized and available to all through a simple user interface on ChatGPT.

    It started with text but is now being used for creating images, audio and videos. 

    It is just the start of the biggest change in humanity we have ever seen. It’s a new gold rush, and it is the new wild west frontier. 

    The post Unveiling 2024 AI Investment Trends: Following the Trillion-Dollar Money Trail appeared first on jeffbullas.com.

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