IsaacL

Benajamin Franklin is a rather fascinating fellow.

Most of us know him from the image that appears on biographies and in textbooks: Franklin with bald pate, round spectacles, and a grandfatherly expression on his face, dispensing homespun wisdom like "early to bed, early to rise", etc, etc.

I.e., he is known as basically the ideal early American pioneer; humble, hard-working, virtuous, and a fount of practical worldly wisdom; working late in his printing shop, setting up volunteer organisations for his fellow citizens, and otherwise being an all-round good guy.

When Franklin was sent to Paris to act as Ambassador for the new United States, many Americans became concerned at what France was doing to him. France was vastly more wealthy and populous than the US at that time, and Paris was notorious as the home of a decadent, libertine elite.

Stories gradually dripped out that Franklin had become quite a party hound, shmoozing with aristocrats and becoming sucked into French high society. He had replaced his modest colonial attire with the height of French aristocratic fashion and powdered wigs. He became a regular in Paris salons and frequently hosted lavish parties in his own residences.

(Indeed, he was already well-known in European intellectual circles for his work on electricity -- Kant called him the "modern Prometheus" -- and so quickly found himself invited to the most exclusive social events, meeting everyone from artists and writers to courtesans and the mistresses of powerful aristocrats.)

Thomas Jefferson -- himself a strong advocate of plain American virtue over decadent European corruption -- was seriously concerned that Franklin was losing his moral compass across the Atlantic. His concerns were only somewhat allayed by the fact that Franklin was securing multiple diplomatic coups, cementing the support of the French monarchy against the British.

(The French Empire was a vital ally of the early US; from the French POV, they were engaged in a titanic struggle for the New World against Britain and Spain, and an independent America was a useful tool in that struggle. But not much prevented France or Spain from carving out chunks of the newly independent US, and Franklin knew America was in a highly vulnerable position between the three imperial powers.)

At any rate, a few years later Franklin returned to Philadelphia and soon reverted to his humble colonial ways, dressing modestly, living simply and acting as a pillar of local society. After his return most dismissed the stories from France as either rumours, greatly exaggerated, or even outright fabrications. The stories didn't fit the Franklin they knew, and besides, the man had evidently secured great advantages for his home country, so why scrutinise his behaviour?

Hindsight tells a different story. As a young man living in London Franklin had learned the hard way the importance of learning to deal with people and the difficulty of adapting to local cultures. (For example, as a young apprentice in a London printing shop, he unknowingly earned the ire of his work colleagues by refusing to contribute to their daily beer budget.)

By his later years he had become a master of social adaptation and of dealing with people from all kinds of backgrounds. In America he acted as a humble, dedicated citizen, devoted to his public duties. In Britain before the revolution he dressed and acted as an ideal English gentleman. When posted in France, he quickly realised the plain-living ways that were encouraged in America would only alienate the French aristocracy, so he adapted his style once again.

It's quite an unusual episode that reveals a more complex, unconventional side to a rather fascinating man.

It was obvious to me as well that your comment was not AI-generated.

I thought I'd reply as I like reading in-depth discussions online, so I don't want to see a future where everyone assumes long comment = AI. :)

There's too many incidental details, too much substance and complexity for this to be an AI-generated comment.

(I know this is an 8-day old thread, but accusing a long comment of being AI-generated is a bad trend.)

I commented about this on X.

As a developer, "infinite scroll to get more digits" sounds really cool. It sounds conceptually similar to lazily-evaluated sequences in languages like Clojure and Haskell (where you can have a 'virtually-infinite' list or array -- basically a function -- and can access arbitrarily large indices).

As a user, it sounds like an annoying interface. On the rare case I want to compute e^(-10000), I do not want to scroll for 3 minutes through screens filled with 0s to find the significant digits.

Furthermore, it's not very usable. A key question in this scenario would be: how many zeroes were there?

It's basically impossible to tell with this UI. A better approach is simply to switch to scientific notation for very large or very small numbers, and leave decimal expansion as an extra option for users who need it. (Roughly similar to what Wolfram Alpha gives you for certain expressions.)

This relates to what I wrote in reply to the original tweet thread.

Performing arithmetic on arbitrarily complex mathematical functions is an interesting area of research but not useful to 99% of calculator users. People who want that functionality with use Wolfram Alpha/Mathematica, Matlab, some software library, or similar.

Most people using calculators are probably using them for budgeting, tax returns, DIY projects ("how much paint do I need?", etc), homework, calorie tracking, etc.

If I was building a calculator app -- especially if I had the resources of Google -- I would start with trying to get inside the mind of the average calculator user and figuring out their actual problems. E.g., perhaps most people just use standard 'napkin math', but struggle a bit with multi-step calculations.

> But for some reason the authors of calculator apps never optimize them for the number of keypresses, unlike Casio/TI/HP. It's a lost art. Even a simple operator repetition is a completely alien concept for new apps.

Yes, there's probably a lot of low-hanging fruit here.

The Android calculator story sounded like many products that came out of Google -- brilliant technical work, but some sort of weird disconnect with the needs of actual users.

(It's not like the researchers ignored users -- they did discuss UI needs in the paper. But everything was distant and theoretical -- at no point did I see any mention of the actual workflow of calculator users, the problems they solve, or the particular UI snags they struggle with.)

This is a terrible article that rambles on for far too long without offering an actually polite way to tell/request someone to do something.

These are the best approaches:

1. "Please take out the trash."

2. "The trash needs to be taken out. Can you do it?"

3. (If there are several people around). "The trash needs to be taken out. Who can do it?"

Extra consideration:

I'm assuming this refers to a context where there's a prior agreement in place that A can tell B what to do (e.g. a business, where B signs a contract stating that he has sold X hours/day to the organisation). It usually should be unnecessary to bark out orders or to beat around the bush -- both are insulting: if B is a functioning adult they accept that they work for an organisation and so need to complete certain tasks.

However, direct instructions are rarely necessary for knowledge workers or highly-skilled professionals. Unless things have broken down horribly, they're aware that the success of the business they work for will contribute to their own career success.

E.g., instead of "you will write unit tests today" or "would you mind terribly writing unit tests today?", A would do best saying something like "we're introducing too many regressions when we change things, we need a better testing strategy -- let's discuss our approach to unit testing" and then let the team weigh in with their own ideas so they have ownership over whatever is decided.

Quotes from the Memo:

"We will distribute tools to leverage the power of these white box models, and create a developer community around our trademark. This approach is an ideological differentiator from OpenAI; it is a very strong point argument for hiring highly coveted top researchers, and a strong accelerator for development, as it will open the doors for many downstream applications from motivated hackers."

So they're trying to build a community of inventive 3rd party developers, however:

"Business development will start in parallel to the first model family development, using the following strategy

- Focus on exploring needs with a large industrial actors, accompanied by third-party integrators that will be given full access to our best (non-open source) model"

Suggests they be will sucked into the enterprise market as I said above. Still, the last line:

"Co-design of products with a few small emerging partners that focuses on generative-AI products."

Suggests a wildcard: one of these "small emerging partners" might come up with the $trillion black-swan application of AI.

[I'm going to bookmark this comment and reread it 2 years from now to see how wrong I was]

I didn't notice that line, but my immediate thought on reading the memo was that they were going hard after European capital. Seemingly both governmental and from VC firms in Europe that are well-connected to the traditional establishment.

(Even if they don't get government funding, it looks like they've already positioned themselves to get a ton of support from the EU and from European national governments, who want local champions to compete with the American capitalists.)

My thoughts:

- it's a fairly well-written memo: clear, concise, and relatively well-structured. It's a refreshing alternative to the endless series of pitch decks which mainly induce groupthink.

- the insights aren't that original. I would guess that they are strongest on the technical level. Their product and industry insights are less original or penetrating (pushing open-source and the European angle may give them some advantages -- it almost certainly will not give them an edge over OpenAI, who seem to have a relentless focus on iterating their product, a "live player" CEO in sama, and a strong dose of healthy scrappiness and creativity.)

- my prediction: they will stick around for a time, build something impressive with their technical team, raise more funding, hire a large and strong technical team (with their enormous warchest, status as the European champion, and appeal to the open-source community), and basically become a solid "fast follower". However, I think it's less certain whether they'll be able to do anything really creative or innovative.

Their overwhelmingly strongest market is going to be large European enterprises (or maybe governments), who will have lots of specific niche problems. The downside of that is their org then moulds itself to fit the needs of enterprise customers.

More speculative: the only way they can really become dangerous will be by attracting a bunch of young top-notch 18-25-year-old devs, ML people, or other builders (basically, people with creative energy and without commitment to the "established ways of doing things"), throwing them in a room together, and giving them a remit to come up with the most crazy, ambitious, unexpected applications of AI that they can. A universal translation app customised for the needs of ERASMUS students. Some weird generative music app for Berlin nightclubs. The actual ideas don't matter, what matters is having 50-100 hyperactive GenZ builders energetically exploring the space of combinations of technology, product and market to identify the genuinely novel applications of AI.

But I predict that they will not do that. You cannot cultivate that kind of free-spirited entrepreneurial DNA while simultaneously seeking deep connections with the European political establishment.

So, my overall prediction: they will focus on the underlying technology and on connections with governments/large enterprises, and deemphasise product innovation. Basically, building an AI-powered French IBM, rather than Google+++++. (Google+++++ will be built by one or two lone young researchers following their noses and working on weird esoteric ideas.) If I am right, and product innovation is the key to harnessing the power of generative models, then these guys in Paris will be formidable but not dangerous.

Should be interesting to watch it play out!

In memory of the olden days when Hacker News focused on discussions for entrepreneurs, here's a question:

I have no doubt that hundreds of millions of BS jobs exist, but isn't that what management consultants are supposed to fix?

Whether or not management consultants actually do fix wasteful jobs is another issue. But my understanding of the sector was that it was aimed to fix these issues. Organisational refactoring, if you will.

Likewise, everyone complains about bad management, but good management is supposed to be able to fix the kind of issues Graeber describes. Steve Jobs' return to Apple in the late 90s is a famous example.

Years ago on this site someone who worked in senior management in a tech company told a story. It went something like this: there were two teams in the company, who were always complaining, not very productive, and seemed to waste enormous amounts of time and energy on pointless busywork or trying to coordinate tasks. Everyone on team A blamed team B, everyone on team B blamed team A, etc, etc. The manager realised this needed to be fixed, talked to the relevant people on both teams, figured out what the problem was, and ... fixed it. (I have no recollection of what the actual problem was -- let's suppose it was some kind of communication or process issue.) After that, things ran smoothly.

Is this story realistic? No doubt -- after all anyone who has worked in engineering is familiar with chronic technical problems that can be fixed with very small amounts of work -- if one has the requisite knowledge. And no doubt there are chronic human problems that are similarly solvable.

Anyway - after many rounds of such management fixes you would have an organisation that ran like a swiss watch. In such places, good managers, like good sysadmins, fade into the background and become invisible. Google in the 2000s may have been a good example. But eventually either the organisation grows, or the good managers leave, or -- most likely -- people decide they no longer need to worry about good management, the organisation begins to rot, and eventually they're forced to bring in bad management. Corporate entropy proceeds in the usual way, and you end up with waste, bad practices, poor communication, doomed projects, crappy output, politics, and -- BS jobs.

This is why I'm skeptical of political intellectuals like Graeber who note a problem but misidentify the solution. Some of the things he categorises as "BS jobs" are themselves intended to fix BS jobs.

But I do not have much experience working in large organisations, so perhaps someone else can chime in.

I asked a follow-up question:

  Where did Person get the spoon from?

ChatGPT's answer:

I apologize for the oversight. Here is the corrected version, including the step to get the spoon:

Person: {The tea is ready. I need a spoon to stir it.} Get a spoon from the kitchen drawer. Computer: You have taken a spoon from the kitchen drawer.

Person: {Now I can stir my tea.} Stir the tea with the spoon. Computer: You have stirred the tea with the spoon.

Person: {Time to enjoy my tea!}

I ran an interesting session with ChatGPT. I don't think the following proves that it has a "world model", but it does seem to be able to emulate having a world model to an impressively high degree of resolution.

I have to snip some prompts for brevity, but here's the gist. I first asked it to list the rooms in a typical apartment and how they are connected. Then I gave it the following prompt:

  Write a table that lists the furniture and other large items that appear in each room. The table should list the name of the item, the room it appears in, its approximate size, and its other attributes.

  Then, create another table that lists the small items that appear in each room. [snipped the rest of the prompt for brevity]

Here is a sample of the output:

  Item Room Size (LxWxH, cm) Attributes

  Sofa Living room 200x90x85 3-seater, upholstered, with cushions

  Coffee table Living room 100x60x45 Wooden, rectangular

  TV Living room 120x6x70 Wall-mounted, flat-screen, 55 inches

  Refrigerator Kitchen 70x70x170 Stainless steel, 300L capacity

And some small items:

  Cushions Living room Sofa 45x45x15 Soft, decorative

  Remote control Living room Coffee table 15x5x2 For TV

  Vase Living room Coffee table 15x15x30 Glass, decorative

  Flowers Living room Vase Varies Fresh or artificial

There were many more rows in the table: I've cut the output down for HN.

I then gave it the following prompt [I included an example of the original SHRDLU in the prompt, which I've cut here]:

  I want you to simulate the classic program SHRDLU by Terry Winograd. SHRDLU functions like above. You will simulate both "Person" and "Computer". "Person" will move around the apartment, pick up a coaster, move to the kitchen, and put the coaster on the kitchen island. After each action of "Person", "Computer" will give one sentence describing the position of the most-recently changed objects.

Output:

Person: Move to the living room. Computer: You are now in the living room.

Person: Pick up a coaster. Computer: You have picked up a coaster from the coffee table.

Person: Move to the kitchen. Computer: You are now in the kitchen.

Person: Put the coaster on the kitchen island. Computer: You have placed the coaster on the kitchen island.

Next prompt:

  Continue to simulate SHRDLU. "Person" goes through the stages to make a cup of tea. There is a bottle of milk in the refrigerator. At each step of the simulation, include "Person"'s thoughts in curly brackets, { }. See the example below. [Example snipped]

Output:

Person: {I feel like having a cup of tea. I need to go to the kitchen, boil water, and gather the necessary supplies.} Move to the kitchen. Computer: You are now in the kitchen.

Person: {I need to boil some water.} Fill the kettle with water. Computer: You have filled the kettle with water.

Person: {Now, let's boil the water.} Turn on the kettle. Computer: The kettle is now on and heating the water.

Person: {While the water is boiling, I'll get a teabag.} Get a teabag from the box of teabags. Computer: You have taken a teabag from the box of teabags.

Person: {Now I need a cup.} Get a cup from the cabinet. Computer: You have taken a cup from the cabinet.

Person: {I'll put the teabag in the cup.} Place the teabag in the cup. Computer: You have placed the teabag in the cup.

Person: {The water should be ready by now.} Pour the boiling water into the cup. Computer: You have poured the boiling water into the cup.

Person: {I need some milk.} Get the bottle of milk from the refrigerator. Computer: You have taken the bottle of milk from the refrigerator.

Person: {I'll add some milk to the cup.} Pour a small amount of milk into the cup. Computer: You have poured a small amount of milk into the cup.

Person: {The tea is ready.} Stir the tea with a spoon. Computer: You have stirred the tea with a spoon.

Person: {Time to enjoy my tea!}

This looks like a very interesting paper that takes the rare approach of actually trying to understand what all the cool new language models are doing at a fundamental level.

Does anyone with more knowledge of the relevant mathematics (group theory and so on) care to chime in?