From OpenAI’s ChatGPT to Google’s creation of its own ChatGPT version (Bard), artificial intelligence is set to revolutionise everything in the modern world. How much are corporate investors willing to put their money at risk with AI technology? And which companies get the lion’s share of these investments?
Investing with AI tools has become increasingly popular in recent years. According to an article by TechJury, 35% of companies are using AI and 42% of companies are exploring AI for its implementation in the future, while 91.5% of leading businesses invest in AI on an ongoing basis.
AI tools provide investors with access to advanced analytics and insights that can help inform their decisions and make them more confident in their decisions. AI tools are able to analyse data quickly and accurately, identify patterns, and make predictions that can be used to guide investment decisions. These can also be used to automate certain aspects of the investing process, such as portfolio rebalancing, which can save investors time and money.
Diving deeper into the layers, writerbuddy.ai analysed over 10,000 AI companies and their funding data between 2015 and 2023 and found that the corporate AI investment has risen consistently to the tune of billions. The investment soared from 12.75 billion dollars in 2015 to 93.5 billion dollars in 2021, marking a remarkable 633.33% increase over the six-year period.
The data was collected from CrunchBase, NetBase Quid, S&P Capital IQ, and NFX.
Comparing the change from 2020 to 2021 with the previous 3 years, where AI investment remained almost consistent, the 2020 pandemic accelerated this growth. Although there was a slight drop in investment volumes in 2018, there has been a recurring boost in investment volumes every year since then. And as consulting firms like McKinsey and Delloite continue to fuel the digital transformation craze and AI becomes more accessible, we expect more investors to fund AI-focused/machine learning operations (MLOps) startups.
The incredible rise of Open AI dominates AI funding. This is a clear sign of the industry’s next giant! OpenAI leads the pack with over $11 billion amassed since its inception, while all the other companies received a combined funding of about $3 billion. However, all 10 of the most funded MLOps startups received over $100 million in funding.
The next most well-funded AI startup was Anthropic. It was founded by OpenAI’s former employees, who aimed to develop more human-like and safe AI. The company raised $1 billion in funding in three rounds. Google is their most recent investor, with $300 million in funding.
Scale AI is a data annotation platform that provides high-quality data to train AI models. Founded in 2016, the company has raised $602.6 million, with the most recent investment round amassing $117 million to support 15 AI projects.
Anyscale is a computing platform that simplifies the development, deployment, and management of Ray applications at scale. Deployed in 2019, the California-based company has secured a total funding of $259 million, with the most recent in August 2022, where they got a $99 million investment.
Inflection AI enables developers to train AI models without sharing that data with anyone. The company was co-founded in 2022 by LinkedIn’s co-founder Reid Hoffman and two others. In its first year, the startup raised an impressive $225 million in one round.
Weights & Biases
Weights & Biases created a developer-first Machine Language Operations platform that offers performance visualisation tools for machine learning. The company has raised $200 million since its inception in 2018 and is valued at $1 billion.
Cohere AI provides affordable and easy-to-deploy large language models that allow computers to read, write, and understand human requests better. The 2019 company raised $164.9 million from institutional venture capital firms like Index Adventures.
Hugging Face develops open-source tools that use machine learning to build applications, like the Transformers library that developers use to create natural language processing applications. The company was founded in 2016 and has raised $160.2 million in five funding rounds. It is currently valued at $2 billion.
OctoML allows developers to deploy machine learning models on any hardware without needing specialised skills. Since the company’s inception in 2019, it has raised $131.9 million in four rounds. Four investors fund OctoML including Madrona Venture Group and Addition.
AI21 Labs created the AI21 Studio, which has language models that rival OpenAI and other natural language processing platforms. As of 2023, AI21 Labs has secured $118.5 million in over six rounds, the latest being $64 million from a Series B round that valued A121 at $664 million.
A spokesperson for writerbuddy.ai commented on this:
“While we can’t predict how robust or accurate AI systems will get in the next few years, one thing is certain; the AI race has just begun. Our findings reveal that AI-focused startups have the potential to raise billions in funding, demonstrating corporate investors’ confidence in Artificial Intelligence. Time will tell who will dominate the space, but OpenAI, with the launch of ChatGPT, seems to be doing everything fine.”
Our future with AI
AI is already being increasingly preferred in businesses to automate tasks, reduce costs, and improve efficiency. It also helps businesses better understand customer behaviour and provide personalised services. With better analysing and forecasting models in place, AI improves the accuracy of predictive analytics.
The potential applications of AI in businesses are virtually limitless. AI can help businesses automate mundane tasks, improve customer service, and drive innovation. AI can also help businesses create more effective marketing campaigns, improve customer experience, and develop new products. AI can also be used to automate processes within the business, allowing for faster and smoother operations. As AI technology continues to improve, businesses will be able to harness the power of AI to create more efficient, cost-effective, and profitable operations.
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