IFTF's Post Financial Futures Forecasts using GPT-3

Worked for years with IFTF (Institute for the Future) in the enterprise.

The Institute for the Future passes along this new GPT-3 Forecast Model, a nice use example.   I will pass along additional findings.

From IFTF: 

We also conducted a groundbreaking experiment using our forecast provocation and OpenAI's GPT-3 to generate over 1,400 live, unique scenarios of post-financialization futures. If you missed it or would like to try out a scenario again the link is here.  

This is an experimental prototype exploring the use of GPT-3 to help augment and customize IFTF’s human forecasting process to broader audiences and more interactive contexts. 

IFTF has pursued this experiment in the spirit of building our literacy of the capabilities and challenges of large language models, and this experiment should not be construed as an endorsement of OpenAI or GPT-3.

IFTF is not responsible for content produced by the large language model GPT-3. The content provided by GPT-3 does not reflect the opinions or views of IFTF.  (Nor of Franz Dill) 

Be sure to mark your calendars for the next IFTF Ten-Year Forecast series event coming up on June 1. We'll be announcing details on expert speakers and special interactive futures immersions very soon.  

Thank you for being a part of IFTF’s TYF community as we look toward shaping a better future!

Our mailing address is:  Institute for the Future,  201 Hamilton Avenue,   Palo Alto, CA 94301  Iftf.org

How Generative AI Could Lower Healthcare Costs, Speed Up Drug Development

 Interesting App in this space, makes much sense. Looking forward to prices going down.

How Generative AI Could Lower Healthcare Costs, Speed Up Drug Development

By ZDNet, March 3, 2023

Absci executives are confident generative AI programs will lead to antibodies with high efficacy in binding to disease targets.

When OpenAI's GPT-3 natural language processing software burst on the scene in 2020, one of the most remarkable things about it was its ability to carry out a variety of tasks in a "zero-shot" fashion. Zero-shot fashion means without having been given any explicit examples of the task, such as printing the French word "rate" when a person types the phrase "translate the word spleen into French," despite never being trained explicitly to translate.

In the near future, AI programs may be able to develop new cancer drugs in a zero-shot fashion, inventing combinations of amino acids that bind to cancer cells and neutralize them with no prior example of an effective protein.

From ZDNet

AI Goal is not Intelligence?

Some thoughts ...

AI's true goal may no longer be intelligence  in ZDNet, Excerpts

Some scholars of AI warn that the present technologies may never add up to "true" intelligence or "human" intelligence. But much of the world may not care about that.

Written by Tiernan Ray, Contributing Writer on Oct. 28, 2022

AI has been rapidly finding industrial applications, such as the use of large language models to automate enterprise IT. Those applications may make the question of actual intelligence moot.

The British mathematician Alan Turing wrote in 1950, "I propose to consider the question, 'Can machines think?'" His inquiry framed the discussion for decades of artificial intelligence research.

For a couple of generations of scientists contemplating AI, the question of whether "true" or "human" intelligence could be achieved was always an important part of the work. 

The emergence of something called industrial AI in recent years may signal an end to such lofty preoccupations. AI has more capability today than at any time in the 66 years since the term AI was first coined by computer scientist John McCarthy. As a result, the industrialization of AI is shifting the focus from intelligence to achievement.

Also: OpenAI's Dall•E 2 may mean we never need stock photos again

Those achievements are remarkable. They include a system that can predict protein folding, AlphaFold, from Google's DeepMind unit, and the text generation program GPT-3 from startup OpenAI. Both of those programs hold tremendous industrial promise irrespective of whether anyone calls them intelligent. 

Among other things, AlphaFold holds the promise of designing novel forms of proteins, a prospect that has electrified the biology community. GPT-3 is rapidly finding its place as a system that can automate business tasks, such as responding to employee or customer queries in writing without human intervention.

That practical success, driven by a prolific semiconductor field, led by chipmaker Nvidia, seems like it might outstrip the old preoccupation with intelligence. 

In no corner of industrial AI does anyone seem to care whether such programs are going to achieve intelligence. It is as if, in the face of practical achievements that demonstrate obvious worth, the old question, "But is it intelligent?" ceases to matter.   ... ' 

Is Having AI Generate Text Cheating?

 Does AI give unfair advantage?   It will come into general use  

Is Having AI Generate Text Cheating?   By Carlos Baquero

Communications of the ACM, December 2022, Vol. 65 No. 12, Pages 6-7    10.1145/3565976

Professor Carlos Baquero of Porto University

https://bit.ly/3ElW1J7   August 3, 2022

Humans were always fragile creatures, most of our success in the ecosystem was driven by the efficient use of new tools. When a new tool arrives that augments our capabilities, we often question the fairness of using it. The debate usually does not last long when the tool has clear benefits. Boats have an advantage over swimming, writing solves our memory problems, this paragraph was improved using a grammar checker, and so forth.

Text generated by AI tools, such as GPT-3 (https://bit.ly/3e3icZQ), has seen an impressive increase in quality, and the AI-generated text is now hard to distinguish from human-generated text. Some people argue that using AI-generated text is cheating, as it gives the user an unfair advantage. However, others argue that AI-generated text is simply another tool that can be used to improve writing. The text in italic type drives this point home, as it was fully AI-generated after giving GPT-3 the appropriate context with the preceding text (going forward in this article, all the AI-generated text is marked in italic). To make the process more confusing, the AI-generated text can be further improved with tools that improve the grammatical presentation and choice of terms. At some point, it becomes hard to distinguish who wrote what.

Blended Writing and Provenance

We can place the question of whether blended writing with AIs will become an acceptable approach to a more efficient use of our capabilities and time. Tools for spelling and grammatical correction are now in everyday use and do not raise any ethical concerns. Nevertheless, AI-generated text, even if accepted from an ethical standpoint, raises questions on the provenance of the generated text. Luckily, there is already an abundance of tools for plagiarism detection (for the purpose of this article, all the AI-generated text has been checked for plagiarism using Quetext (https://bit.ly/3rrCy1U)). In the case of GPT-3, a closed-book system with no access to external content after the pre-training phase, the generation of "ipsis verbis" text seems statistically unlikely for any long output, so the plagiarism check is likely an abundance of care.

OpenAI, owner of GPT-3, does provide guidelines (https://bit.ly/3fvsnXd) for content co-authored with GPT-3. The gist is: Do no harm, refrain from using harmful content; clearly identify the use of AI-generated content; attribute it to your name, you are responsible for the published content. ... 

Excerpt  .. 

Will AI Kill College Writing?

 I think still pretty detectable. 

Will AI Kill College Writing?

By The Chronicle of Higher Education

October 3, 2022

Each time you click GPT-3's “submit” button, the machine learning algorithm pulls from the wisdom of the entire Internet and generates a unique output, so that no two end products are the same.

When I was a kid, my favorite poem was Shel Silverstein's "The Homework Machine," which summed up my childhood fantasy: a machine that could do my homework at the press of a button. Decades later that technology, the innocuously titled GPT-3, has arrived. It threatens many aspects of university education — above all, college writing.

The web-based GPT-3 software program, which was developed by an Elon Musk-backed nonprofit called OpenAI, is a kind of omniscient Siri or Alexa that can turn any prompt into prose. You type in a query — say, a list of ingredients (what can I make with eggs, garlic, mushrooms, butter, and feta cheese?) or a genre and prompt (write an inspiring TED Talk on the ways in which authentic leaders can change the world) — and GPT-3 spits out a written response. These outputs can be astonishingly specific and tailored.

From The Chronicle of Higher Education

View Full Article  

Pitching Your Startup to a robot.

 Found this case study of how you might pitch a new startup to a GPT-3 Based robot, called Pitchexpert.

I pitched my ridiculous startup idea to a robot VC,    By Luke Dormehl  in DigitalTrends

September 1, 2022 6:30AM

Aqua Drone. HighTides. Oh Water Drone Company. H2 Air. Drone Like A Fish. Whatever I called it, it was going to be big. Huge. Well, probably.

It was the pitch for my new startup, a company that promised to deliver one of the world’s most popular resources in the most high-tech way imaginable: an on-demand drone delivery service for bottled water. In my mind I was already picking out my Gulfstream private jet, bumping fists with Apple’s Tim Cook, and staging hostile takeovers of Twitter. I just needed to convince a panel of venture capitalists that I (and they) were onto a good thing.

There were three VCs in total. The good news was that at least one of them already loved my idea. But he still had a few pointers. I should, they suggested, focus on a niche market, whether that be athletes, office workers, or music festival attendees. They also wanted me to do a better job articulating why people should buy water from a drone rather than just picking it up at the store. Fair enough, I suppose. Not everyone can quite envision the widespread appeal of bottled water from the sky.  ... ' 

(Read the whole thing for results)  .... 

Are Chatbots Just an Illusion?

Good test and challenge of current 'best' performing AI, with comments. 

The AI Illusion – STATE-OF-THE-ART CHATBOTS AREN’T WHAT THEY SEEM

GPT-3 is very much like a performance by a good magician

By Gary Smith March 21, 2022  In Mindmatters

Artificial intelligence is an oxymoron. Despite all the incredible things computers can do, they are still not intelligent in any meaningful sense of the word.

Decades ago, AI researchers largely abandoned their quest to build computers that mimic our wondrously flexible human intelligence and instead created algorithms that were useful (i.e., profitable). Despite this understandable detour, some AI enthusiasts market their creations as genuinely intelligent. For example, a few months ago, Blaise Aguera y Arcas, the head of Google’s AI group in Seattle, argued that “statistics do amount to understanding.” As evidence, he cites a few exchanges with Google’s LaMDA chatbot. The examples were impressively coherent but they are still what Gary Marcus and Ernest Davis characterize as “a fluent spouter of bullshit” because computer algorithms do not understand what words mean. They are like Nigel Richards, who has won several French-language Scrabble championships without knowing the meaning of the words he spells.

Google’s LaMDA is not accessible by the general public — which makes me wonder how robust it is. On January 3 of this year, I reported using OpenAI’s powerful chatbot GPT-3 to illustrate the fact that statistics do not amount to understanding. Andrew Gelman challenged Arcas to try my examples with LaMDA but Arcas has not responded, nor has anyone at Google, presumably because they are not permitted to. 

A few days ago, a student sent me a link to an OpenAI description of GPT-3. One candid disclaimer was that, “GPT-3 is not necessarily well-calibrated in its predictions on novel inputs.” Being able to understand and react to novel situations is, in fact, a benchmark of genuine intelligence. Until computer algorithms can do that, AI will remain an oxymoron.

OpenAI’s description also revealed that,

InstructGPT is then further fine-tuned on a dataset labeled by human labelers. The labelers comprise a team of about 40 contractors whom we hired through Upwork and ScaleAI.

Lack of real-world grounding: GPT-3, like other large pretrained language models, is not grounded in other modalities of experience, such as video, real-world physical interaction, or human feedback, and thus lacks a large amount of context about the world.

OpenAI evidently employs 40 humans to clean up GPT-3’s answers manually because GPT-3 does not know anything about the real world. Intrigued, I retried the questions that GPT-3 had flubbed in January to see if the labelers had done their job.  ..... ' 

More on No-Code

Yes will continue to emerge, and decrease security

 No-Code' Brings the Power of AI to the Masses

The New York Times,Craig S. Smith, March 15, 2022

"Citizen developers" are tapping products that allow anyone to use artificial intelligence (AI) without writing any computer code, as part of the "no-code" movement envisioned by advocates as revolutionary. "We are trying to take AI and make it ridiculously easy," said Craig Wisneski at the startup Akkio, which lets anyone make predictions using data. No-code platforms replace coding languages with simple and familiar Web interfaces, and new startups are making the power of AI available to nontechnical people in visual, textual, and audio spheres. The Juji tool, for example, is engineered to simplify chatbot building, by using machine learning to automatically manage complex conversation flows and deduce user characteristics to personalize each engagement. The power of no-code platforms is also growing through AI innovations such as OpenAI's GPT-3 system, which can write code when prompted with simple English.

Full Article.

Businesses Offerred OpenAI By Microsoft.

Microsoft built an API for its use.   Seems it needs some cautions due to liability.

Microsoft is giving businesses access to OpenAI’s powerful AI language model GPT-3

A promising and problematic AI tool

By James Vincent  Nov 2, 2021, 11:00am EDT

It’s the AI system once deemed too dangerous to release to the public by its creators. Now, Microsoft is making an upgraded version of the program, OpenAI’s autocomplete software GPT-3, available to business customers as part of its suite of Azure cloud tools.

GPT-3 is the best known example of a new generation of AI language models. These systems primarily work as autocomplete tools: feed them a snippet of text, whether an email or a poem, and the AI will do its best to continue what’s been written. Their ability to parse language, however, also allows them to take on other tasks like summarizing documents, analyzing the sentiment of text, and generating ideas for projects and stories — jobs with which Microsoft says its new Azure OpenAI Service will help customers.

Here’s an example scenario from Microsoft:

“A sports franchise could build an app for fans that offers reasoning of commentary and a summary of game highlights, lowlights and analysis in real time. Their marketing team could then use GPT-3’s capability to produce original content and help them brainstorm ideas for social media or blog posts and engage with fans more quickly.”

GPT-3 is already being used for this sort of work via an API sold by OpenAI. Startups like Copy.ai promise that their GPT-derived tools will help users spruce up work emails and pitch decks, while more exotic applications include using GPT-3 to power a choose-your-own-adventure text game and chatbots pretending to be fictional TikTok influencers.

While OpenAI will continue selling its own API for GPT-3 to provide customers with the latest upgrades, Microsoft’s repackaging of the system will be aimed at larger businesses that want more support and safety. That means their service will offer tools like “access management, private networking, data handling protections [and] scaling capacity.” ( see cautions for its use at the link ..._)

OpenAI Codex Turns Written Language Into Computer Code

 How different than LoCode?

OpenAI's Codex Turns Written Language Into Computer Code

By Axios, August 11, 2021

OpenAI is releasing an improved version of its Codex AI model that can read written instructions in conversational language and transform it into working computer code.

The model is the latest example of progress in natural language processing, and points toward a future in which coders will be able to offload some of their work to AIs, and where ordinary people may be able to code without programmer training.

Codex is a descendant of OpenAI's text-generating model GPT-3. While GPT-3 was trained on a huge quantity of language data taken from the Internet, Codex was trained on both language and billions of lines of publicly available computer code.

As a result, users can issue commands in written English, and Codex will produce computer code capable of carrying out those instructions, essentially making it an English-to-Python (or any of more than a dozen programming languages in Codex's training data) computer code translator.

From Axios

View Full Article

Microsoft Aims to Make Low-Code Easier

Been examining some of the evolving Low and No code options for delivering coded logic Here Microsoft's aims in the space.

Microsoft to make coding 'in plain English' easier with PowerFx and GPT-3 AI model

Microsoft's integration of the OpenAI GPT-3 technology into Power Apps is the first time GPT-3 will be available commercially in one of its own products.     By Mary Jo Foley for All About Microsoft | Topic: Artificial Intelligence

Microsoft is integrating AI technologies with its PowerFx low-code programming language. This integration will enable customers to use natural-language input and "programming by example" techniques when developing with PowerApps.

Microsoft announced the coming new capabilities during the opening day, May 25,  of its virtual Build 2021 developers conference. Officials said these new features will be in public preview in English throughout North America by the end of June.  ... ' 

China Claims to Exceed GPT-3 Language

Continued push on more powerful language models.

China outstrips GPT-3 with even more ambitious AI language model

By Anthony Spadafora   in TechRadar,  First Published 2 weeks ago

WuDao 2.0 model was trained using 1.75tn parameters

A Chinese AI institute has unveiled a new natural language processing (NLP) model that is even more sophisticated than those created by both Google and OpenAI.

The WuDao 2.0 model was created by the Beijing Academy of Artificial Intelligence (BAAI) and developed with the help of over 100 scientists from multiple organizations. What makes this pre-trained AI model so special is the fact that it uses 1.75tn parameters to simulate conversations, understand pictures, write poems and even create recipes.

Parameters are variables that are defined by machine learning models and as these models evolve, the parameters themselves also improve to allow an algorithm to get better at finding the correct outcome over time. Once a model has been trained on a specific data set like human speech samples, the outcome can then be applied to solving other similar problems.  ... " 

LaMDA: Next Generation Chatbots

Short intro to Google's LaMDA.   Looking for smarter conversations.  Hope to use this in  upcoming applications.

Google’s LaMDA: The Next Generation of Chatbots

First, we had GPT-3. Now we have LaMDA.,    By Alberto Romero

In mid-2020 OpenAI presented the all-powerful language system GPT-3. It revolutionized the world and landed headlines in very important media outlet magazines. This incredible technology can create fiction, poetry, music, code, and many other amazing things (I wrote a complete overview of GPT-3 for Towards Data Science if you want to check it out).

It was expected that other big tech companies wouldn’t fall behind. Indeed, some days ago at Google I/O annual conference, Google executives presented the last research and technologies of the big firm. One of them stole the show: LaMDA, a conversational AI capable of having human-like conversations.

In this article, I’m going to review the little we know today about this tech and how it works.

LaMDA — A conversational AI

LaMDA stands for “Language Model for Dialogue Applications.” Following from previous models such as BERT and GPT-3, LaMDA is also based on the transformer architecture, open-sourced by Google in 2017. This architecture allows the model to predict text focusing only on how previous words relate to each other (attention mechanism).  ... '

Advances in Language-Based AI Tasks

Not surprising,  language is communications.  Between us and everything else.  Spent lots of time trying to make that work.

Advances in Language-Based AI Tasks Seen as Dawn of New Era    By AI Trends Staff  

Researchers at Accenture have found that 10% of early adopters of digital technologies have grown at twice the rate of the bottom 25%, and they are using cloud systems—not legacy systems—to enable adoption.  

H. James Wilson, Managing Director, Accenture:

“We expect the trend to accelerate among industry leaders over the coming five years,” stated the authors, H. James Wilson and Paul R. Daugherty, in an account in Harvard Business Review. And more specifically, following the release of the GPT-3 large language model from Open AI, “The 2020s will be about major advances in language-based AI tasks,” the authors suggest. 

Generative pre-trained transformers (GPTs) rely on a transformer, a mechanism that learns contextual relationships between words in a text, state the authors, who are coauthors of the book, Human + Machine:Reimagining Work in the Age of AI (Harvard Business Review Press). 

Despite flaws in GPT-3 including producing nonsense or biased responses and generating plausible but false content, “A new age of AI is upon us,” the authors state 

Microsoft, Google, Alibaba, and Facebook are all working on their own version of “advanced transformers.” The tools will be trained in the cloud and accessible via APIs. “Companies that want to harness the power of next generation AI will shift their compute workloads from legacy to cloud-AI services like GPT-3,” the authors suggest.  

This will enable a new class of enterprise applications that will make the process of synthesizing words and information in language cheaper. Based on an analysis of more than 50 business-relevant proof of concept applications of GPT-3, the authors see three broad categories linked to language understanding: writing, coding and discipline-specific reasoning.  

For example, GPT-3 is capable of converting natural language to programming language. It can plot graphs based on verbal descriptions. One beta tester created a GPT-3 bot that enables people with no accounting skills to generate financial statements.   ... ' 

Machines Writing for Us

Will such robotic systems do all our writing for us?  A lot of words being spewed.

OpenAI’s text-generating system GPT-3 is now spewing out 4.5 billion words a day

Robot-generated writing looks set to be the next big thing

By James Vincent in The Verge

One of the biggest trends in machine learning right now is text generation. AI systems learn by absorbing billions of words scraped from the internet and generate text in response to a variety of prompts. It sounds simple, but these machines can be put to a wide array of tasks — from creating fiction, to writing bad code, to letting you chat with historical figures. ... " 

Generating Visual Images from Text Descriptions

Something we could have used to test visual understanding of products and their use.  

OpenAI’s latest neural network creates images from written descriptions  By Ryan Daws | January 6, 2021 | TechForge Media

Categories: Neural Network, OpenAI, Society,

Editor at TechForge Media. Often sighted at global tech conferences with a coffee in one hand and laptop in the other. If it's geeky, I'm probably into it.

OpenAI has debuted its latest jaw-dropping innovation, an image-generating neural network called DALL·E   ....   a 12-billion parameter version of GPT-3 which is trained to generate images from text descriptions.

“We find that DALL·E is able to create plausible images for a great variety of sentences that explore the compositional structure of language,“ OpenAI explains.   Generated images ca range from drawings, to objects, and even manipulated real-world photos. Here are some examples of each provided by OpenAI:  ... 

Quest for More Common Sense: Less Thinking?

Nicely put piece that connects with the current state of the technology.   And shows some of the  challenges.  Have been involved in a number of attempts at including common sense in reasoning, without general success.  Back to our need for strong context based reasoning made in the last post.  Most succinctly its knowledge and context with a causal engine.

The quest for artificial common sense   By Samuel Flender in TowardsDataScience

On July 19th, a blog post titled ‘Feeling unproductive? Maybe you should stop overthinking.’ appeared online. The 1000-word self-help article explains that overthinking is the enemy of our creativity, and advises us to be more in the moment:

“In order to get something done, maybe we need to think less. Seems counter-intuitive, but I believe sometimes our thoughts can get in the way of the creative process. We can work better at times when we ‘tune out’ the external world and focus on what’s in front of us.”

The post was written by GPT-3, Open AI’s massive 175-Billion-parameter neural network trained on nearly half a Trillion words. UC Berkeley student Liam Porr merely wrote the title, and let the algorithm fill in the text. A ‘fun experiment’, to see whether the AI could fool people or not. Indeed, GPT-3 hit a nerve: the post was up-voted to the top of Hacker News.

There’s a paradox, then, with today’s AI. While some of GPT-3’s writings arguably meet the Touring test criterion — convincing people that it is human — it fails spectacularly at the simplest tasks. AI researcher Gary Marcus asked GPT-2, the precursor to GPT-3, to complete the following sentence: ... ' 

Singularity Hub Looks at GPT-3

Out of SingularityHub.   A look at the writing AI called GPT-3.  Scopes some of the possibilities and limitations.

OpenAI’s GPT-3 Wrote This Short Film—Even the Twist at the End  By Vanessa Bates Ramirez

OpenAI’s text generating AI has gotten a lot of buzz since its release in June. It’s been used to post comments on Reddit, write a poem roasting Elon Musk, and even write an entire article in The Guardian (which editors admitted they worked on and tweaked just as they would a human-written op ed).

When the system learned to autocomplete images without having been specifically trained to do so (as well as write code, translate between languages, and do math) it even got people speculating whether GPT-3 might be the gateway to artificial general intelligence (it’s probably not).

Now there’s another feat to add to GPT-3’s list: it wrote a screenplay.

It’s short, and weird, and honestly not that good. But… it’s also not all that bad, especially given that it was written by a machine.

The three-and-half-minute short film shows a man knocking on a woman’s door and sharing a story about an accident he was in. It’s hard to tell where the storyline is going, but surprises viewers with what could be considered a twist ending.  ... " 

Numenta Research Meeting: A Look at GPT-3

 Also a talk on GPT-3 of interest  ...

Numenta Research Meeting: “Steve Omohundro on GPT-3”    by omohundro  On July 1, 2020, Steve Omohundro gave a talk on GPT-3 and it's implications for artificial intelligence to Numenta's Research Meeting: In this research meeting, guest Stephen Omohundro gave a fascinating talk on GPT-3, the new massive OpenAI Natural Language Processing model. He reviewed the network architecture, training process, and results in the context of […]

Microsoft Licenses OpenAI’s GPT-3 Language Model

Exclusively.  Now this is very good and somewhat unexpected.   Thinking of ways it might be used within the context of work needs in Teams.    Say for example constructing documents that describe the agreements made a meeting.   Or summarize results.   Is it good enough to do those things?  More at the link.

Microsoft gets exclusive license for OpenAI’s GPT-3 language model   By Kyle Wiggers  in VentureBeat

 Microsoft today announced that it will exclusively license GPT-3, one of the most powerful language understanding models in the world, from AI startup OpenAI. In a blog post, Microsoft EVP Kevin Scott said that the new deal will allow Microsoft to leverage OpenAI’s technical innovations to develop and deliver AI solutions for customers, as well as create new solutions that harness the power of natural language generation.

“We see this as an incredible opportunity to expand our Azure-powered AI platform in a way that democratizes AI technology, enables new products, services and experiences, and increases the positive impact of AI at scale,” Scott wrote. “The scope of commercial and creative potential that can be unlocked through the GPT-3 model is profound, with genuinely novel capabilities — most of which we haven’t even imagined yet. Directly aiding human creativity and ingenuity in areas like writing and composition, describing and summarizing large blocks of long-form data (including code), converting natural language to another language — the possibilities are limited only by the ideas and scenarios that we bring to the table.”    ... "