3 ways AI is Already Transcending Hype and Delivering Tangible Results

3 ways AI is already transcending hype and delivering tangible results

Peter Evans, Xtract One Technologies    in Vneturebeat

@XtractOne, July 15, 2023 8:20 AM

Google search trends for AI have soared since the service launched, and companies are rushing to lap up domains from Anguilla, population 15,000, looking to benefit from its .ai domain registration. 

At the same time, investors are pouring money into generative AI startups, hoping to catch lightning in a bottle and capitalize on this technology to find the next big tech breakthrough. As one AI investor recently told the New York Times, “We’re in that phase of the market where it’s, like, let 1,000 flowers bloom.” 

Today, the hype cycle is so hot that even companies without legitimate AI credentials are trying to align themselves with the technology, prompting the Federal Trade Commission to issue a terse warning to companies: “If you think you can get away with baseless claims that your product is AI-enabled, think again.”

The hype cycle can be so ludicrous that Axios reporter Felix Salmon recently explained, “When a company starts talking loudly about its AI abilities, the first question should always be: “Why is this company talking loudly about its AI abilities?”

To be sure, this isn’t the first rodeo for AI speculation. The technology is more than half a century old, and it’s been through many boom and bust cycles that yielded significant technological advances but have continually failed to fully live up to the hype. 

In other words, developing AI products and services that are repeatable, scalable and sellable has historically been difficult and often prohibitively expensive. However, by looking at the ways AI is already making the most significant impact, we can paint a clearer and possibly more accurate picture of what it will look like moving forward. 

Here are three ways AI is impacting our world today, which can provide a useful roadmap for how it might actually change the world tomorrow.  ...  '

How AI Is Building the Next Blockbuster Videogames

Building better yet Video Games with AI. And how might we build better yet games that represent a means for constructing embedded games that solve for true value reports.   Seeing the opportunity for that.

How AI Is Building the Next Blockbuster Videogames

By The Wall Street Journal, April 25, 2023

ChatGPT-like technology is being used to develop games faster and make them more interactive.

Videogame companies are using generative artificial intelligence (AI) tools to create next-generation games faster, at less cost, and with more advanced interactivity.

Electronic Arts is employing generative AI to produce digital sketches for visualizing concepts like challenges and game levels in hours rather than weeks.

Meanwhile, Roblox is developing its own generative AI tools to help developers build new types of materials and movements on screen via text prompts.

Ubisoft Entertainment's Ghostwriter AI tool writes first drafts of background or nonplayable characters' chatter.

Industry executives doubt the technology will replace human developers, who are required to input the prompts and to refine the results.

From The Wall Street Journal

View Full Article - 

ChatGPT provides results

Testing alternative solution:

When ChatGPT was asked about what results it had achieved, and how,  it responded:

Here are some key results and statistics related to the development and use of large language models such as ChatGPT:

Large language models like ChatGPT are typically trained on massive amounts of text data, such as books, articles, and websites. For example, the original version of GPT-3, the predecessor to ChatGPT, was trained on a dataset of over 570GB of text.

The development of large language models has led to significant advances in natural language processing (NLP) and has enabled new applications such as chatbots, virtual assistants, and content generation.

The largest and most powerful language model to date is GPT-3, which was released in 2020 by OpenAI. GPT-3 has 175 billion parameters, making it the largest language model by far.

Large language models have shown impressive results in a variety of NLP tasks, such as language modeling, language translation, and sentiment analysis. For example, GPT-3 has been shown to be capable of generating human-like text, completing text prompts, and answering questions with high accuracy.

The development of large language models has raised concerns about ethical and societal implications, such as bias in training data, algorithmic discrimination, and the potential misuse of AI-generated text. It is important to carefully consider and address these concerns as large language models continue to advance.

Large language models require significant computational resources and energy to train and operate. This has led to concerns about the environmental impact of AI, as well as the potential for unequal access to AI technology due to high costs.

Large language models are a rapidly evolving technology, and research and development in this area is ongoing. New models with even larger parameters are currently under development, and it is likely that this technology will continue to advance in the coming years. ...   END