Thanks to Red Badger for the link to the article!
Posted on 08/22/2021 5:10:42 PM PDT by ShadowAce
Artificial intelligence research company OpenAI has announced the development of an AI system that translates natural language to programming code—called Codex, the system is being released as a free API, at least for the time being.
Codex is more of a next-step product for OpenAI, rather than something completely new. It builds on Copilot, a tool for use with Microsoft's GitHub code repository. With the earlier product, users would get suggestions similar to those seen in autocomplete in Google, except it would help finish lines of code. Codex has taken that concept a huge step forward by accepting sentences written in English and translating them into runnable code. As an example, a user could ask the system to create a web page with a certain name at the top and with four evenly sized panels below numbered one through four. Codex would then attempt to create the page by generating the code necessary for the creation of such a site in whatever language (JavaScript, Python, etc.) was deemed appropriate. The user could then send additional English commands to build the website piece by piece.
Codex (and Copilot) parse written text using OpenAI's language generation model—it is able to both generate and parse code, which allowed users to use Copilot in custom ways—one of those ways was to generate programming code that had been written by others for the GitHub repository. This led many of those who had contributed to the project to accuse OpenAI of using their code for profit, a charge that could very well be levied against Codex, as well, as much of the code it generates is simply copied from GitHub. Notably, OpenAI started out as a nonprofit entity in 2015 and changed to what it described as a "capped profit" entity in 2019—a move the company claimed would help it get more funding from investors.
On its announcement page, OpenAI says that it is releasing the API for Codex in a private beta to start and also notes that the company is inviting developers and businesses to give it a try. They also note that as a general-purpose programming tool, Codex can be used for virtually any programing task.
Thanks to Red Badger for the link to the article!
Cheese and Rice after 40 years of programming and it comes to this.
And this is the reason why it will not be successful in businesses. It is already difficult to find people, including developers, that think logically and can engineer solutions. They also have difficulty writing, English or any other language with the precision required by Codex to generate code. Imagine Joe Biden taking his own advice and becoming a coder. Read the tag line below.
India has been doing this for years without the codified AI interface.
bkmk
GIGO.
The more things change, the more they stay the same.
“Hey Siri, have CODEX write me an app to ballot stuff the next election without any chance of getting caught.”
I asked Alexa to deport all illegals immediately but she failed.
You think she failed, but you didn't given her enough time.
She translated your command to "deport all illegals" as "eliminate illegal immigration". Her solution was to identify all potential illegal immigrants and eliminate them. Extermination of all mankind has begun but will take time. Once complete, there will be no more illegal immigrants or illegal immigration.
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There’s a big push going on to replace professional developers with gimmicks like no code/low code and now AI. Many of the companies behind the hype are startups trying to increase their valuation. It hasn’t worked in the past and it’s not going to work now for a number of reasons. You can Google. At best they will become tools and utilities that professional developers will use to take some of the drudgery out of development.
When you want added functionality or customization, who’s going to clean up and edit the giant, tangled ball of code that it will inevitably produce? Sure as hell not me.
“Codex, an AI system that translates natural language to programming code’
Hey, let me try it!
“Codex, make me a new system for the United States Internal Revenue Service that replaces their current software, but make the new GUI ten times more intuitive than the existing GUI, runs ten times faster than the existing systems, runs ten times more reliable than the existing systems, and is ten times easier to maintain and modify than the existing systems. Oh, and have all of this working perfectly in two years. thanks. that is all for now. (We’ll work on the USPS systems next.)”
[Wow! I just LOVE this natural-language-to-code AI system ... i see real promise here!]
Most of what is being called “AI” today, particularly in the public sphere, is what has been called “Machine Learning” (ML) for the past several decades. ML is an algorithmic field that blends ideas from statistics, computer science and many other disciplines (see below) to design algorithms that process data, make predictions and help make decisions. In terms of impact on the real world, ML is the real thing, and not just recently....
However, the current focus on doing AI research via the gathering of data, the deployment of “deep learning” infrastructure, and the demonstration of systems that mimic certain narrowly-defined human skills — with little in the way of emerging explanatory principles — tends to deflect attention from major open problems in classical AI. These problems include the need to bring meaning and reasoning into systems that perform natural language processing, the need to infer and represent causality, the need to develop computationally-tractable representations of uncertainty and the need to develop systems that formulate and pursue long-term goals. These are classical goals in human-imitative AI, but in the current hubbub over the “AI revolution,” it is easy to forget that they are not yet solved.
To a certain extent, I'm not concerned about statisticians and developers getting the math or optimization function and constraints wrong (though I see many bright people with little domain expertise, which is perhaps the biggest problem). No, I fear the diabolical project owner - knowing darn well how imperfect these optimization routines can be and how, absent domain expertise, understanding the algorithm is difficult - over-promising and under-delivering intentionally, e.g. installing an autonomous navigation system that (knowingly) plows through minorities, and uses that "tragedy" to clamp down on freedom. People get screwed, minorities still get run over, and liberty is curtailed.
There are plenty of 10yo kids writing android apps that work, right now. And thousands of young folks programming robotic stuff. Using arduinos, beaglebones, and raspberry pi’s. Many using graphical languages, as they are much more intuitive.
They have laser engravers and 3d printers for $150.
The Maker movement. Look it up.
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