Gartner AI Hype Cycle Offers NEW Technologies To Watch
The recently published 2023 Gartner Artificial Intelligence Hype Cycle gives us clues to new AI technologies and possibly NEW LEADERS.
Published: August 25, 2023 | Published By: Real Creative Agency
Before starting this deep dive, readers will see a critically important mention of the First Principles way of thinking later in this presentation.
Many of Elon Musk’s successes in the business world are attributed to these principles, and the respected Gartner group just added them in their 2023 AI Hype Report, along with VERSES AI being publicly traded company proven to bring this process to the AI world by way of intelligent and thinking software!.
Gartner 2023 Artificial Intelligence Hype Cycle Highlights
The recently published 2023 Gartner Artificial Intelligence Hype Cycle give us clues to new AI innovations and possibly the new leaders.
When you want to do something new, you have to apply the [first principles] approach.”..Elon Musk…
REMEMBER THAT TERM….”First Principle”.
Diving in on the chronology, here’s how the AI boom started, the obstacles it just started facing, and what could be the leading form of AI.
Blog Post Menu
- AI Industry Summary
- Is AGI Close?
- A GENERATIVE AI Bubble?
- Generative AI Industry
- AI Leaders
- Gartner Hype Cycle
- Gartner AI Hype Cycle
- First Principle AI
- Multi Agent System
- This Is The Way
Artificial Intelligence Industry Summary
Diving in on the chronology, here’s how the AI boom started and the obstacles it just started facing, along with what could be the leading form of AI.
Nov 30, 2022: OpenAI launches ChatGPT, the world’s first large language model-based chatbot.
Jan 1, 2023: ChatGPT records 100M users, the FASTEST growth app ever.
Jan 23, 2023: Microsoft invests $10B in OpenAI, giving it a valuation of $29B
Feb 23, 2023: VERSES announces GIA, a Next Generation AI Intelligent Agent. This is MONTHS before Bill Gates mentions the idea of an “AI personal agent.”
March 2, 2023: Google launches its AI chatbot Bard
Quarter ONE 2023: Venture capital ramps funding in generative ai. At least 13 generative unicorns ($1B valuation) were created.
May 16, 2023: Sam Altman, CEO of OpenAI testifies before Congress on AI risks. However, he sidesteps suggestions, such as requirements for transparency in training data.
May 24, 2023: NVIDIA (Ai chip company) posts record earnings.
Founder and CEO says “The computer industry is going through two simultaneous transitions — accelerated computing and generative AI.” “A trillion dollars of installed global data center infrastructure will transition from general purpose to accelerated computing as companies race to apply generative AI into every product, service and business process.” “ We are significantly increasing our supply to meet surging demand for them,” he said.
May 22, 2023: Bill Gates said a personal digital agent could kill Google Search and Amazon. The first company to develop it will have a leg up on competitors.
May 22, 2023: European watchdog fines Meta (Facebook) $1.3B over privacy violations. A sign the EU will be cracking down on regulating AI next?
May 24, 2023: VERSES AI files a patent application covering a milestone invention for automating the generation of intelligent software agents directly from data sets that can interact with both software and hardware systems, such as robots, drones, sensors and actuators.
May 25, 2023: OpenAI’s Sam Altman threatens to leave EU if he doesn’t like their ChatGPT regulation
May 30, 2023: NVDA stock reaches trillion dollar market cap (FIRST chip company to achieve this)
June 5, 2023: VERSES, DENTONS US and SWF, collectively announce Collaboration on Landmark Industry Report: “The Future of Global AI Governance”
This report combines the legislative expertise from the world’s largest multinational law firm… Dentons, VERSES’s AI acumen, and guidance on technical standards from the Spatial Web Foundation.
Uniting to provide an in-depth analysis of the legal and key legislative trends from across the world on the state of AI regulation and recommendations for a path forward for government regulation of AI.
June 7, 2023: OpenAI is hit with first defamation suit over ChatGPT
June 8, 2023: European Union takes a major step in regulating AI with the EU AI Act. This is the world’s FIRST major regulation legislation on artificial intelligence.
Explainable AI (XAI) – the AI system’s ability to explain or to provide the meaning in “understandable” terms to an individual, while another relates it to traceability from input data to the output.
As a result, Generative AI like ChatGPT, would have to comply with transparency requirements.
June 8, 2023: VERSES AI publishes a landmark research paper articulating methods for developing human-interpretable, explainable artificial intelligence (XAI) systems based on active inference and the Free Energy Principle, which offers new possibilities for transparency and understanding of AI processing.
The research proposes a unique AI architecture based on the active inference framework and the Free Energy Principle. These scientific principles can be used to create an AI that can explain its decision-making process in human-understandable terms – a significant advancement in the era of ‘Explainable AI.
AGI May Be Closer Than Gartner Forecasts
June 12, 2023: VERSES AI CEO says “We believe that we’re the only company in the world actually building AGI right now” (Video)….but Gartner is forecasting more than 10 years?
June 14, 2023; The EU passes Artificial Intelligence Regulation Bill
June 14, 2023: McKinsey says, “Generative AI’s impact on productivity could add between $17T to $25.6T in value to the global economy,”
June 22, 2023: CEO of Stability AI says Ai could bring the “biggest bubble of all time” and also states, “it hasn’t even started yet.”
Is It ONLY A GENERATIVE AI Bubble?
Regulations and legal issues appear to be putting the brakes on generative AI, but what if there is innovative technology that could solve these issues for EXISTING and NEWLY CREATED content?…stay tuned.
July 9, 2023: Sarah Silverman and other novelists sue ChatGPT and Meta over copyright violations
July 12, 2023: Google hit with lawsuit alleging it stole data from millions of user to train its AI tools
July 12, 2023: Elon Musk launches his new company xAI, with the stated goal to “understand the true nature of the universe”.
July 13, 2023: The FTC investigates OpenAI. The company could be fined up to $150,000 for each piece of copyrighted material used to train the language model.
July 25, 2023: Forbes says “AI driven bubble” may burst and drag down the stock market.
August 16, 2023; N.Y. Times considers legal action against OpenAI (ChatGPT) for copyright violations.
August 17, 2023: Axios article highlights legal risk of AI. Users can be liable for chatbot mistakes.
August 21, 2023: DC Court says NO copyright registration for works created by Generative AI.
August 22,2023: FTC warns deceptive AI content violates the FTC Act.
What’s happening with Generative AI Industry
Using home building as an analogy, here’s an easy way to explain what happened with Generative AI.
Imagine a bunch of homebuilders constructing new homes on a property that was expected to be the most valuable location in the world. Also, A TON of homes were built on this location.
A few months after the homes were built, a study came out and determined that the drywall used contains a very harmful product like asbestos, and regulatory agencies are set to fine every builder that used this drywall. In essence, they could get fined for EVERY sheet in EVERY home.
What you have now is a bunch of new homes that can’t be sold, and nobody wants to buy them, understandably so!
On the flip side, if there were a solution that could remove asbestos or meet the upcoming regulations, it would probably be in great demand… wouldn’t you think?
Keep pondering that question.
Are Artificial Intelligence Leaders Emerging?
Remember the “Free Principle” from earlier?
August 7, 2023: Free Energy Principle… the E=mc2 of intelligence.
Simply put, the Law of Intelligence is proven, OR a first principle for ALL intelligence but it can also be applied to artificial intelligence.
August 7, 2023: Elon Musk thinks Tesla could have made a significant advance in AI, with the introduction of more advanced AI algorithms in their vehicles.
When you want to do something new, you have to apply the [first principles] approach.”..Elon Musk
The Gartner Hype Cycle
Gartner is a leading technological research and consulting firm that offers clients actionable advice on developing strategies, selecting technologies, and implementing them in their businesses.
Their “hype cycle” is a graphical presentation forecasting the maturity, adoption, and social application of specific technologies. New technologies get added or dropped, and timelines for each stage can also change.
Early stage investors (VCs) use this to identify NEW technologies to invest in, where they are on the cycle, and determine future funding for their existing investments.
The ideal investment is a NEW technology that is an “Innovation Trigger” with LESS THAN 2 years to “Plateau of Productivity.”
It consists of five phases that a technology typically goes through:
- Innovation Trigger: This is the initial phase where a new technology is introduced. There’s often a lot of excitement and media attention, but the practical applications and potential pitfalls are not fully understood.
- Peak of Inflated Expectations: In this phase, there’s a rapid rise in expectations, leading to exaggerated optimism about the technology’s capabilities. This can result in a “hype” where the technology is seen as a panacea for various challenges.
- Trough of Disillusionment: As the initial excitement fades, reality sets in, and the limitations and challenges of the technology become apparent. This can lead to disappointment, decreased interest, and even skepticism.
- Slope of Enlightenment: In this phase, a more balanced understanding of the technology’s value and limitations emerges. Through experimentation and practical application, the true potential becomes clearer, and successful use cases are identified.
Plateau of Productivity: Finally, the technology reaches a stage of stability and widespread adoption. Its benefits are well understood, and it becomes integrated into various industries and applications, contributing to a substantial positive impact.
Venture capital (VC) investors often play a significant role in the early phases of the Gartner Hype Cycle, particularly during the “Innovation Trigger” and “Peak of Inflated Expectations” stages.
KEYPOINT: Don’t let the terms “Hype Cycle” and “Peak of Inflated Expectations” confuse you. The typical “sweet spot” for VC funding is 7 years to reach the plateau of productivity.
2023 Gartner Artificial Intelligence Hype Cycle
August 17, 2023: Gartner publishes the annual 2023 Artificial Intelligence Hype Cycle.
We identified 3 Key points this year.
This includes 2 new Innovation Triggers (First-Principles AI + Multiagent Systems), and the timeline for Plateau to Productivity for Generative AI was PUSHED BACK.
1. First Principles AI (FPAI) was added to the cycle with an estimated LESS THAN 2 YEARS adoption time.
In other words, FPAI is expected to offer a VC-like return in LESS TIME than generative ai.
2. The plateau of productivity for Generative AI was PUSHED OUT from 2- 5 yrs in 2022, to 5-10 years.
The Plateau of Productivity is when major adoption and abundant revenue is generated, and we start to take the product for granted.
3. “Multiagent Systems” was added this year with the same timeframe PoP as Generative AI.
(MAS) is a type of AI system composed of multiple, independent (but interactive) agents, each capable of perceiving their environment and taking actions. Agents can be AI models, software programs, robots and other computational entities.
Read more: Gartner’s what’s new in artificial intelligence.
What is the First Principle of Artificial Intelligence?
First-principles AI (FPAI) (physics-informed AI) incorporates physical and analog principles, governing laws, and domain knowledge into AI models.
The first principle thinking is often associated with Elon Musk, who uses this approach to develop his business ideas, create innovative product designs, and build winning products that positively impact society.
When you want to do something new, you have to apply the [first principles] approach.”..Elon Musk
Here’s a simplified explanation of first principle thinking:
- First principles are the basic building blocks of something. For example, the first principles of a car are things like wheels, an engine, and a steering wheel.
- With the application of first principles here, Generative AI is like the “wheels” and FPAI will be the “engine”.
The first PRINCIPLE of AI is based on the Law of intelligence.
The law of intelligence is the Free Energy Principle. Likewise, it’s a PROVEN physics based way to describe how intelligence works.
Why FPAI was added to Gartner AI Hype Cycle:
- Could enable other forms of AI
- Can scale more easily than Generative AI
- Has the potential to be more powerful and robust than Generative AI, which could make it a more attractive investment for venture capitalists.
- Has the potential to be a major breakthrough in AI.
- Could enable the $25T GDP increase forecasted by McKinsey.
- Enables the things that Generative AI needs to be adopted
- Has the potential to make AI more accurate, reliable and powerful.
KEYNOTE: VERSES’ software platform is based on FPAI
When we Google “first principles ai systems,” there are 2 articles referencing VERSES and their Chief Scientist Dr. Karl Friston.
Search first principles ai systems for yourself.
These are the articles to look for.
Read an interpretation of the white paper “Designing Ecosystems of Intelligence from First Principles” released by VERSES Research Labs and translated into simple-to-understand language and concepts.
What is an AI Multi Agent System?
This is a new class of Agents that have the capacity to evaluate and consider their responses before making them, and to assess the context of a scenario before determining an appropriate course of action.
In essence, it enables AI to be able to “think” before they speak or act and to constantly learn and update their understanding of users, and the domain they operate in.
This is a significant development in AI, allowing agents to be more intelligent and adaptable.
In the past, AI agents were often limited to following pre-programmed instructions. But with this new development, agents can learn and adapt to new situations, making them more useful and reliable.
A multi-agent system (MAS) is a system composed of multiple agents that interact with each other to achieve a common goal.
In the case of kids playing baseball, each kid is an agent. The kids have their own goals, such as getting on base or hitting a home run, but they also need to work together to achieve the common goal of winning the game.
The kids can communicate with each other and share information. They can also coordinate their actions, such as when to run to first base or field a fly ball.
The kids need to be able to adapt to changes in the game, such as when the other team makes a good play or when the weather changes.
Ants are a great example of a multi-agent system.
Each ant is an individual agent, but they work together to achieve a common goal, such as building a nest or finding food.
Ants communicate with each other using pheromones, which are chemical signals that they leave behind. The pheromones can be used to mark trails, to communicate danger, or to attract other ants.
Ants also coordinate their actions through indirect communication. For example, if an ant finds food, it will start to carry it back to the nest. This will attract other ants, who will also start to carry food back to the nest. This process is called stigmergy.
Ants can adapt to changes in their environment through a process called self-organization. This means that they can change their behavior without any central control.
For example, if an ant finds a new food source, it will start to communicate this information to other ants. This will eventually lead to all of the ants in the colony moving to the new food source.
Multi-agent systems are inspired by the way that ants work together. They are used in various applications, such as traffic control, manufacturing, and robotics.
Here are some examples of multi-agent systems:
- A traffic control system that uses sensors to monitor traffic and then sends signals to traffic lights to control the flow of cars.
- A factory floor that uses robots to assemble products. The robots communicate with each other to coordinate their actions.
- A game of soccer where the players work together to score goals.
- A multi-agent system can be used to power e-commerce websites.
- A multi-agent system can be used to manage a power grid
VERSES filed a patent application covering a milestone invention for automating the generation of intelligent software agents directly from data sets that can interact with both software and hardware systems, such as robots, drones, sensors and actuators.
By automating the process of creating agents, this technology could make it possible to create agents that are more intelligent, adaptable and scalable, than ever before.
This is a unique approach to creating adaptable and context-aware intelligent agents, which sets it apart from models like ChatGPT in terms of its underlying principles and intended functionality.
This is The Way
BILLIONS have been invested in Generative AI companies, and they now face IMMEDIATE risks (regulatory and legal).
The world’s largest law firm, DENTONS, and most respected venture capital firm, Gartner, along with VERSES AI, have outlined what could solve this trillion-dollar problem.
The AI space is already at a pivotal moment in its infancy, and maybe this is the way!?
So ask yourself… are we in an “AI bubble,” or could regulations and innovative technology be creating the leaders in the AI space?
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