{"id":1489,"date":"2023-11-26T19:47:34","date_gmt":"2023-11-26T19:47:34","guid":{"rendered":"https:\/\/zeppscommentaries.online\/?p=1489"},"modified":"2023-11-26T19:47:34","modified_gmt":"2023-11-26T19:47:34","slug":"quadrophobia-working-the-numbers","status":"publish","type":"post","link":"https:\/\/zeppscommentaries.online\/?p=1489","title":{"rendered":"Quadrophobia — Working the Numbers"},"content":{"rendered":"

Quadrophobia<\/b><\/p>\n

Working the Numbers<\/b><\/p>\n

Bryan Zepp Jamieson<\/i><\/p>\n

November 26th<\/sup>, 2023<\/i><\/p>\n

www.zeppscommentaries.online<\/i><\/p>\n

In the huge uproar surrounding the sudden sacking, and even more unexpected rehiring of Sam Altman at ChatGPT, and the revitalization of discussion over the benefits and perils of Artificial Intelligence, there was a throw-away line in one article that seized my attention.<\/p>\n

The line stated, with no elaboration, that their AI program had solved a math formula problem that it hadn\u2019t seen before. Being a mainstream media source, it didn\u2019t elaborate, since numbers bigger than about six hurt readers, make branes hurt.<\/p>\n

Michael Parekh on his blog \u201cAI: Reset to Zero\u201d elaborated in a much more meaningful way:<\/p>\n

\u201cIn the following months, senior OpenAI researchers used the innovation to build systems that could solve basic math problems, a difficult task for existing AI models. Jakub Pachocki and Szymon Sidor, two top researchers, used Sutskever\u2019s work to build a model called Q* (pronounced \u201cQ-Star\u201d) that was able to solve math problems that it hadn\u2019t seen before, an important technical milestone. A demo of the model circulated within OpenAI in recent weeks, and the pace of development alarmed some researchers focused on AI safety.<\/em><\/p>\n

\u201cThe work of Sutskever\u2019s team, which has not previously been reported, and the concern inside the organization, suggest that tensions within OpenAI about the pace of its work will continue even after Altman was reinstated as CEO Tuesday night, and highlights a potential divide among executives. (See more about the <\/em>safety conflicts<\/a><\/strong> at OpenAI.)<\/em><\/p>\n

\u201cLast week, Pachocki and Sidor were among the first senior employees to resign following Altman\u2019s ouster. Details of Sutskever\u2019s breakthrough, and his concerns about AI safety, help explain his participation in Altman\u2019s high-profile ouster, as well as why Sidor and Pachocki resigned quickly after Altman was fired. The two returned to the company after Altman\u2019s reinstatement.\u201d <\/em>( https:\/\/michaelparekh.substack.com\/p\/ai-doing-the-reasoning-math-reliably<\/a> )<\/em><\/p>\n

Solving previously unseen math problems is HUGE. It involves extrapolative logic, something computers have not been able to accomplish. <\/em>The vast majority of humans can\u2019t manage that. I\u2019m going to give you an example:<\/em><\/p>\n

3 + 14t \u2212 5t<\/em>2<\/sup><\/em> = 0<\/em><\/p>\n

OK, most of you will recognize that with widely varying degrees of fondness from middle school or perhaps high school. It\u2019s called a quadratic, and it was a sneaky introduction to the basics of calculus. Most teachers couldn\u2019t be arsed to explain what those were for back in my day, and the best ones would come up with seemingly incoherent examples, such as measuring the perimeter area of a room around a carpet, or what happens if you toss a ball in the air at a certain speed. There are, in fact, a lot of occupations where they can be massively useful, but for most <\/em>students<\/em> they were just an annoying form of sudoku. Just to add to the general merriment, qua<\/em>d<\/em>ratics had two solutions, one of which was physically impossible. In this case, the solutions are t =\u2212<\/em>0.2 or t = 3. Three is the one that is possible. You could make a graph from quadratics which is where my brane broke and it had to be sent off to the knackers. I was left with a choice: be an innumerate annoying smart-ass, or be a Republican. You decide.<\/em><\/p>\n

Now suppose you had never ever seen a quadratic before in your life. Would you be able to figure out what its purpose was? From that, could you solve it, knowing you would have to factor it and possibly use the imaginary number <\/em>i<\/i><\/em>, the square root of minus one? <\/em><\/p>\n

Hell, most of you DID take quadratics in grade seven, taught by Ben Stein\u2019s boring brother, and you couldn\u2019t even begin to start on it. I did, but I admit I looked up the answer to make sure I hadn\u2019t embarrassed myself. Just don\u2019t ask me to draw a chart. The results would probably be painful for both of us.<\/em><\/p>\n

OK, so this algor<\/em>i<\/em>thm looked at some math function it hadn\u2019t seen before, and, understanding only the variables, the operatives, and the numbers themselves, worked out the correct answer on its own. I don\u2019t know that it was a quadratic that was the formula or what, but it represents a huge step forward, the first time a computer has demonstrated autonomous intellectual logic. <\/em><\/p>\n

There are a lot of very genuine concerns about AI (I recently read a very good SF novel about an AI tasked with preparing the North American West Coast against a Cascadian fault movement of 9.0, forestalling the quake itself by planned explosives and moving fifty or so million people out of harm\u2019s way. Someone made the horrible mistake of feeding the AI <\/em>a<\/em> concept <\/em>of Occam\u2019s Razor, \u201cThe simplest solution is usually the best.\u201d Armed with that, the AI realizes the smart and efficient thing is to just let \u2018er rip, cost less, and have much less rebuilding to do afterward because there would be less people. <\/em>So it let the earthquake proceed.<\/em>) <\/em><\/p>\n

Of course AI has been a popular notion in SF going back to the first robot novel, \u201cRUR,\u201d back in 1927. Even in the 60\u2019s, it was assumed that if you just gave a computer enough processing power and data, it would \u201cwake up,\u201d like Mycroft Holmes <\/em>(Mike)<\/em> in Heinlein\u2019s \u201cThe Moon is a Harsh Mistress.\u201d It\u2019s clearly much more involved then that (even back then, I viewed the \u201cwake up\u201d notion as being similar to stacking hamburger meat seven feet high and getting a basketball player). <\/em><\/p>\n

But it also appears that the point of self-awareness is now very near, and autonomous decision making really does need something like Isaac Asimov\u2019s Three Laws of Robotics: <\/em><\/p>\n