With artificial intelligence impacting just about every industry in the world, the market could be worth about $594 billion by 2032, according to Precedence Research. All of which could have a powerful impact on AI-related stocks, such as VERSES AI (CBOE: VERS) (OTCQB: VRSSF), Nvidia (NASDAQ: NVDA), Microsoft (NASDAQ: MSFT), Meta (NASDAQ: MSFT), and Advanced Micro Devices (NASDAQ: AMD). In fact, AI has already helped many companies around the world improve efficiency, reduce costs, and increase accuracy.
In addition, according to a McKinsey report, “63% of companies that adopted AI into their operations in 2023 reported revenue increases.” Plus, “Artificial intelligence in business operations is expected to double the efficiency of the workforce and boost profitability by an average of 38% by 2035, according to Accenture's prediction.” And, according to IBM, “In 2024, it's estimated that businesses will interact with their customers more through AI-powered communication channels than human-led efforts.”
Plus, as noted by analysts at Bank of America, the AI boom could boost the global economy by about $15.7 trillion by 2030. "We are at a defining moment - like the internet in the '90s - where Artificial Intelligence (AI) is moving towards mass adoption, with large language models like ChatGPT finally enabling us to fully capitalize on the data revolution," said the firm, as quoted by Business Insider.
Look at VERSES AI Inc. (CBOE: VERS) (OTCQB: VRSSF), For Example
VERSES AI Inc., a cognitive computing company developing next-generation intelligent software systems, today provides a research roadmap that outlines the key milestones and benchmarks against which to measure the progress and significance of the Company’s research and development efforts, against advanced deep learning, for the benefit of industry, academia, and the public.
“We laid out a roadmap that can be accessed at https://www.verses.ai/rd-overview, which we expect to use to demonstrate over the course of this year that VERSES’ approach to AI is able to match or exceed the performance of advanced AI models on multiple industry-standard benchmarks while using materially less data and energy," said Gabriel René, founder and CEO of VERSES.
This is notable in light of OpenAI’s CEO Sam Altman’s recent statement that the future of AI depends on an energy breakthrough along with a plan to raise $7 Trillion to reshape the global semiconductor industry.
Mr. René further stated, “The implications of meeting these benchmarks is to provide scientific evidence that VERSES’ approach can yield better, cheaper and faster AI that applies to a broader market opportunity and commercialized in our Genius Platform. We have published our research roadmap so that both the industry and the public can track our progress.”
First benchmark: Classification and generation tasks
With the first benchmark, VERSES intends to demonstrate the compute and sample efficiency on image classification and generation tasks such as MNIST and CIFAR; in particular, demonstrating the computational efficiency of VERSES’ approach over and above other advanced Bayesian inference toolboxes, such as NumPyro. We also intend to show how this approach is competitive with the computational efficiency of traditional deep learning approaches based on tools like PyTorch—but augmented with the great sample efficiency that comes from adopting a fully Bayesian approach. The Company plans to release these results demonstrating the efficient compute and improved sample efficiency of our approach to classification and generation tasks around the end of Q1–Q2 2024 in open-access publications.
Second benchmark: Atari 10k Challenge
With the second benchmark, the Atari 10K Challenge, intends to demonstrate that VERSES’ approach is vastly more sample and compute efficient than other alternatives. The initial Atari benchmark challenge was introduced in 2015 and involved producing a single AI system that could meet or beat human-level performance on 26 classic Atari games. The AI model must learn directly from pixel data, using only the score as a reward signal. The initial architecture designed for this was data-heavy, using years of gameplay—usually more data than a human player might ever have access to.
To address this, the Atari 100k benchmark was introduced, which restricts the amount of gameplay used in learning to 100,000 environment steps. While Atari 100k is a good benchmark to showcase the power and sample efficiency properties of the active inference approach. The Company expects to demonstrate two sources of gains in efficiency. The first comes from fast online learning of the world model for the game. The second comes from efficient policy estimation that does not require periodic resets of the sort used by current advanced gradient-based methods, such as Q-learning.
Although the Atari 100k (2 hours of gameplay) is the industry-leading benchmark, and VERSES plans to demonstrate competitive play at the 100k benchmark, the Company intends to further showcase the unique strengths of active inference-based AI, namely, rapid learning and improved sample efficiency by proposing the Atari 10k benchmark challenge (roughly 12 minutes of gameplay), using only raw pixel data and the score as input. The challenge is to reach human-level performance (or greater) measured on the same amount of gameplay. Humans can achieve competent play very quickly, but how do advanced architectures perform? VERSES intends to demonstrate that our system can outperform advanced deep learning on the 10k benchmark—learning to play the game efficiently with little data. Our preliminary results currently demonstrate that our agents are able to learn the dynamics of gameplay and score on simple games in only several thousand steps, demonstrating more efficient learning using a model that is ninety-nine percent smaller in parameter size than the leading competitors, and able to train on a laptop without a large GPU infrastructure.
The Company plans to share final results in Q3 2024, as well as in open-access publications.
Third benchmark: NeurIPS 2024 Melting Pot Challenge
The previous two benchmarks cater to the strengths of deep learning approaches, i.e., they often involve noiseless tasks that are completely observed (with no ambiguity) and that involve well-defined reward functions.
Therefore these benchmarks do not showcase the power of active inference. For the third benchmark, VERSES intends to use the new multi-agent NeurIPS Melting Pot Challenge benchmark since the ultimate goal is to develop more naturalistic benchmarks that showcase the ability of active inference agents to deal with uncertain environments.
Specifically, one of the main advantages of building active inference agents that work directly in belief space with an explicit representational structure is that it becomes possible to share beliefs between agents.
The Company believes that this benchmark will showcase the benefits that active inference brings for engineering multi-agent systems and align with the central ambitions of VERSES AI research: to create ecosystems of AI systems.
VERSES plans to share these results showcasing the unique ability of active inference agents to lay the foundations of smart multiagent systems around Q4 2024–Q1 2025, additionally in open-access publications.
Other related developments from around the markets include:
Nvidia reported revenue for the fourth quarter ended January 28, 2024, of $22.1 billion, up 22% from the previous quarter and up 265% from a year ago. For the quarter, GAAP earnings per diluted share was $4.93, up 33% from the previous quarter and up 765% from a year ago. Non-GAAP earnings per diluted share was $5.16, up 28% from the previous quarter and up 486% from a year ago. For fiscal 2024, revenue was up 126% to $60.9 billion. GAAP earnings per diluted share was $11.93, up 586% from a year ago. Non-GAAP earnings per diluted share was $12.96, up 288% from a year ago. “Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations,” said Jensen Huang, founder and CEO of NVIDIA.
Microsoft announced results for the quarter ended December 31, 2023, as compared to the corresponding period of last fiscal year: Revenue was $62.0 billion and increased 18% (up 16% in constant currency). Operating income was $27.0 billion and increased 33%, and increased 25% non-GAAP (up 23% in constant currency). Net income was $21.9 billion and increased 33%, and increased 26% non-GAAP (up 23% in constant currency). Diluted earnings per share was $2.93 and increased 33%, and increased 26% non-GAAP (up 23% in constant currency). "We’ve moved from talking about AI to applying AI at scale," said Satya Nadella, chairman and chief executive officer of Microsoft. "By infusing AI across every layer of our tech stack, we’re winning new customers and helping drive new benefits and productivity gains across every sector.”
Meta Platforms reported financial results for the quarter and full year ended December 31, 2023. "We had a good quarter as our community and business continue to grow," said Mark Zuckerberg, Meta founder and CEO. "We've made a lot of progress on our vision for advancing AI and the metaverse." Revenue was $40.11 billion and $134.90 billion, an increase of 25% and 16% year-over-year for the fourth quarter and full year 2023, respectively. Had foreign exchange rates remained constant with the same periods of 2022, revenue would have been $816 million and $374 million lower, an increase of 22% and 15% on a constant currency basis for the fourth quarter and full year 2023, respectively.
Advanced Micro Devices announced revenue for the fourth quarter of 2023 of $6.2 billion, gross margin of 47%, operating income of $342 million, net income of $667 million and diluted earnings per share of $0.41. On a non-GAAP) basis, gross margin was 51%, operating income was $1.4 billion, net income was $1.2 billion and diluted earnings per share was $0.77. For the full year 2023, the company reported revenue of $22.7 billion, gross margin of 46%, operating income of $401 million, net income of $854 million and diluted earnings per share of $0.53. On a non-GAAP) basis, gross margin was 50%, operating income was $4.9 billion, net income was $4.3 billion and diluted earnings per share was $2.65.
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