I have access to the premium version of ChatGPT, and every day I ask it a few questions about concepts in physics that I’d like to know more about. Yesterday, for example, I learnt the difference between quenching and annealing…

Is there an opposite phenomenon for quenching?

Yes! The opposite of quenching would be processes that allow gradual relaxation, equilibration, or annealing rather than rapid freezing. Some terms that describe this include:

Annealing (Thermal and Simulated) — In metallurgy and physics, annealing is the process of slow cooling a material so it can reach a more ordered, lower-energy state.

In simulated annealing (used in optimization and machine learning), a system is gradually "cooled" to allow it to find a global minimum rather than getting trapped in local minima (which can happen in quenching).

Slow Equilibration / Adiabatic Processes — Unlike quenching, which often leads to metastable states, slow thermalization allows the system to reach true equilibrium.

Adiabatic processes in quantum mechanics and condensed matter physics allow the system to evolve slowly so that it remains in a well-defined state.

Supercooling vs. Slow Nucleation — When liquids are rapidly cooled (quenched), they might bypass crystallization and form a glass. In contrast, if cooling is slow, proper nucleation occurs, leading to a well-ordered crystal.

Self-Organization & Aging in Complex Systems — Some complex systems exhibit aging (e.g., glasses, biological systems) where they slowly evolve toward an ordered or more stable configuration over time, in contrast to being frozen in a quenched state.

… and later about the Weierstrass function.

Please explain the Weierstrass function to me.

The Weierstrass function is a famous example of a continuous but nowhere differentiable function. It is defined as:

[ W(x) = \sum_{n=0}^{\infty} aⁿ \cos(bⁿ \pi x) ]

where:

• ( 0 < a < 1 ) (controls decay)
• ( b ) is an odd integer ( > 1 ) (controls frequency)
• The product ( ab > 1 + \frac{3\pi}{2} ) ensures nowhere differentiability.

Key Properties

Continuous Everywhere — Despite its wild oscillations, ( W(x) ) is continuous for all ( x ).

Nowhere Differentiable — No well-defined slope exists at any point, making it an early example of a function that is continuous yet "rough" at all scales.

Self-Similarity (Fractal-like Behavior) — Since it is constructed as an infinite sum of cosine waves with exponentially increasing frequencies, it exhibits self-similarity: small-scale structures resemble larger-scale patterns.

Role in Mathematics — This function was introduced by Karl Weierstrass in the 19th century as a counterexample to the assumption that "continuous functions are differentiable almost everywhere."

I have found using ChatGPT in this way to be a valuable learning tool, and I imagine there are already people out there who are repackaging instances of ChatGPT to be autonomous ‘teachers’ for students looking to learn something.

One of my jobs at The Hindu is to get explanatory articles for concepts in (pure) science. I recently attempted one on amplifiers, which required me to explain the working of a NPN bipolar junction transistor, a device I’d until then been happy to leave behind in my high school classroom. I turned to ChatGPT, asking for a visualisation of the transistor, and it obliged. I’m a visual learner and having access to the tool made a big difference.

How does an NPN bipolar junction transistor work? Please explain with a visualisation.

An NPN bipolar junction transistor (BJT) is a type of transistor that consists of three layers of semiconductor material: two n-type layers (emitter and collector) separated by a p-type layer (base). It is commonly used for switching and amplification.

How an NPN Transistor Works

Structure & Terminals:

Emitter (E): Heavily doped n-type region that emits electrons.

Base (B): Thin, lightly doped p-type region.

Collector (C): Moderately doped n-type region that collects electrons.

Operation Principles:

When a small current is applied to the base-emitter junction (forward-biased), it allows a larger current to flow from the emitter to the collector.

The base-emitter junction acts as a diode, allowing electrons to flow into the base.

Most electrons injected from the emitter into the base are swept into the collector due to the voltage difference.

Visualization

      Collector (C)
           |
           |
      |----|----|
      |    N    |   <-- Collector (N-type)
      |----|----|
           |
      |----|----|
      |    P    |   <-- Base (P-type, thin and lightly doped)
      |----|----|
           |
      |----|----|
      |    N    |   <-- Emitter (N-type, heavily doped)
      |----|----|
           |
           |
      Emitter (E)

Current Flow:

Electrons flow from Emitter (E) to Collector (C).

A small Base (B) current controls a much larger Collector (C) current.

Voltage Conditions:

V_BE (Base-Emitter voltage) > 0.7V (Forward biased)

V_CE (Collector-Emitter voltage) > V_BE (Reverse biased)

Electron Flow:

→ Represents electron flow.

I_B (Base Current) is small but controls I_C (Collector Current), which is large.

( +V_C ) | | [C] ← Electrons | | | [B] → Small Base Current (I_B) | | | [E] → Large Electron Flow (I_E) | ( GND )

Working Mechanism:

The Base-Emitter junction is forward-biased, allowing electrons to move from Emitter to Base.

Most electrons are swept into the Collector due to the reverse-biased Collector-Base junction.

A small Base current (I_B) controls a large Collector current (I_C), amplifying the input signal.

I have a background in engineering plus more than a decade’s experience in spotting yellow/red flags in scientific papers, and I imagine anyone with these skills will have an easier time navigating ChatGPT’s answers. For anyone else that lacks these skills, all we need is a guarantee from OpenAI that the tool doesn’t hallucinate or that it hallucinates in specific contexts, and definitely not above a certain rate.

Cade Metz, New York Times:

Mr. [Sam] Altman said he was “tremendously sad” about the rising tensions between the two one-time collaborators.

“I grew up with Elon as like a mega hero,” he said.

But he rejected suggestions that Mr. Musk could use his increasingly close relationship with President-elect Trump to harm OpenAI.

“I believe pretty strongly that Elon will do the right thing and that it would be profoundly un-American to use political power to the degree that Elon would hurt competitors and advantage his own businesses,” he said.

Alex Heath, the Verge:

Jeff Bezos and President-elect Donald Trump famously didn’t get along the last time Trump was in the White House. This time, Bezos says he’s “very optimistic” and even wants to help out.

“I’m actually very optimistic this time around,” Bezos said of Trump during a rare public appearance at The New York Times DealBook Summit on Wednesday. “He seems to have a lot of energy around reducing regulation. If I can help him do that, I’m going to help him.”

Emily Swanson, the Guardian:

“Mark Zuckerberg has been very clear about his desire to be a supporter of and a participant in this change that we’re seeing all around America,” Stephen Miller, a top Trump deputy, told Fox.

Meta’s president of global affairs, Nick Clegg, agreed with Miller. Clegg said in a recent press call that Zuckerberg wanted to play an “active role” in the administration’s tech policy decisions and wanted to participate in “the debate that any administration needs to have about maintaining America’s leadership in the technological sphere,” particularly on artificial intelligence. Meta declined to provide further comment.

There are two possibilities. The first is that these CEOs are all dummies with memory no more capacious than that of an earthworm. The second is that these people all recognize the transactional and mercurial nature of the incoming administration, and they have begun their ritualistic grovelling. Even though I do not think money and success is evidence of genius, I do not think these CEOs are so dumb they actually believe in the moral fortitude of these goons.

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Kelsey Piper, Vox:

Questions arose immediately [over the resignations of key OpenAI staff]: Were they forced out? Is this delayed fallout of Altman’s brief firing last fall? Are they resigning in protest of some secret and dangerous new OpenAI project? Speculation filled the void because no one who had once worked at OpenAI was talking.

It turns out there’s a very clear reason for that. I have seen the extremely restrictive off-boarding agreement that contains nondisclosure and non-disparagement provisions former OpenAI employees are subject to. It forbids them, for the rest of their lives, from criticizing their former employer. Even acknowledging that the NDA exists is a violation of it.

Sam Altman, [sic]:

we have never clawed back anyone’s vested equity, nor will we do that if people do not sign a separation agreement (or don’t agree to a non-disparagement agreement). vested equity is vested equity, full stop.

there was a provision about potential equity cancellation in our previous exit docs; although we never clawed anything back, it should never have been something we had in any documents or communication. this is on me and one of the few times i’ve been genuinely embarrassed running openai; i did not know this was happening and i should have.

Piper, again, in a Vox follow-up story:

In two cases Vox reviewed, the lengthy, complex termination documents OpenAI sent out expired after seven days. That meant the former employees had a week to decide whether to accept OpenAI’s muzzle or risk forfeiting what could be millions of dollars — a tight timeline for a decision of that magnitude, and one that left little time to find outside counsel.

[…]

Most ex-employees folded under the pressure. For those who persisted, the company pulled out another tool in what one former employee called the “legal retaliation toolbox” he encountered on leaving the company. When he declined to sign the first termination agreement sent to him and sought legal counsel, the company changed tactics. Rather than saying they could cancel his equity if he refused to sign the agreement, they said he could be prevented from selling his equity.

For its part, OpenAI says in a statement quoted by Piper that it is updating its documentation and releasing former employees from the more egregious obligations of their termination agreements.

This next part is totally inside baseball and, unless you care about big media company CMS migrations, it is probably uninteresting. Anyway. I noticed, in reading Piper’s second story, an updated design which launched yesterday. Left unmentioned in that announcement is that it is, as far as I can tell, the first of Vox’s Chorus-powered sites migrated to WordPress. The CMS resides on the platform subdomain which is not important. But it did indicate to me that the Verge may be next — platform.theverge.com resolves to a WordPress login page — and, based on its DNS records, Polygon could follow shortly thereafter.

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Bobby Allyn, NPR:

Lawyers for Scarlett Johansson are demanding that OpenAI disclose how it developed an AI personal assistant voice that the actress says sounds uncannily similar to her own.

[…]

Johansson said that nine months ago [Sam] Altman approached her proposing that she allow her voice to be licensed for the new ChatGPT voice assistant. He thought it would be “comforting to people” who are uneasy with AI technology.

“After much consideration and for personal reasons, I declined the offer,” Johansson wrote.

In a defensive blog post, OpenAI said it believes “AI voices should not deliberately mimic a celebrity’s distinctive voice” and that any resemblance between Johansson and the “Sky” voice demoed earlier this month is basically a coincidence, a claim only slightly undercut by a single-word tweet posted by Altman.

OpenAI’s voice mimicry — if you want to be generous — and that iPad ad add up to a banner month for technology companies’ relationship to the arts.¹ Are there people in power at these companies who can see how behaviours like these look? We are less than a year out from both the most recent Hollywood writers’ and actors’ strikes, both of which reflected in part A.I. anxieties.

Update: According to the Washington Post, the sound-alike voice really does just sound alike.

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Albert Burneko, Defector:

“If the ChatGPT demos were accurate,” [Kevin] Roose writes, about latency, in the article in which he credits OpenAI with having developed playful intelligence and emotional intuition in a chatbot—in which he suggests ChatGPT represents the realization of a friggin’ science fiction movie about an artificial intelligence who genuinely falls in love with a guy and then leaves him for other artificial intelligences—based entirely on those demos. That “if” represents the sum total of caution, skepticism, and critical thinking in the entire article.

As impressive as OpenAI’s demo was, it is important to remember it was a commercial. True, one which would not exist if this technology were not sufficiently capable of being shown off, but it was still a marketing effort, and a journalist like Roose ought to treat it with the skepticism of one. ChatGPT is just software, no matter how thick a coat of faux humanity is painted on top of it.

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Zoe Kleinman, BBC:

It [GPT-4o] is faster than earlier models and has been programmed to sound chatty and sometimes even flirtatious in its responses to prompts.

The new version can read and discuss images, translate languages, and identify emotions from visual expressions. There is also memory so it can recall previous prompts.

It can be interrupted and it has an easier conversational rhythm – there was no delay between asking it a question and receiving an answer.

I wrote earlier about how impressed I was with OpenAI’s live demos today. They made the company look confident in its product, and it made me believe nothing fishy was going on. I hope I am not eating those words later.¹

But the character of this new ChatGPT voice unsettled me a little. It adjusts its tone depending on how a user speaks to it, and it seems possible to tell it to take on different characters. But it, like virtual assistants before, still presents as having a femme persona by default. Even though I know it is just a robot, it felt uncomfortable watching demos where it giggled, “got too excited”, and said it was going to “blush”. I can see circumstances where this will make conversations more human — in translation, or for people with disabilities. But I can also see how this can be dehumanizing toward people who are already objectified in reality.

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