Ever since I discovered the Discord server for AI music generation, I knew I needed to train a model to make my voice a great singer. It took some figuring out, but now I'm having a lot of fun making myself sing every kind of song. I've tried dozens now, but here are some ones that are particularly notable or fun (I find it funniest when things glitch out especially around the high notes):

When people visit my website, it's not very clear to them what it is I actually do. It used to be that my website doubled as my CV, but after a while that became sort of useless as I no longer needed to apply to jobs, and I stopped maintaining it.

Recently, I began revamping the landing page of my website (yet again) and started off by cleaning up the hero section. I had a bunch of icons that represented links, and thought I was being clever and language-agnostic by using icons instead of text, but then realised that even I was forgetting what icon meant what, so I couldn't begin to hope that others would know what they meant. So I added text. And I made the WebGL avatar have an image fallback in case the browser doesn't support WebGL. Similarly, I froze the parallax effects under the same conditions as those rely on hardware acceleration.

Then, I decided to create a project grid right under the hero. I wanted to treat this as a showcase of the things I am involved in, or have been involved in, loosely in order of importance. This has been inspired by:

• Philipp Lenssen, from whom I originally got the idea, and realised the tiles don't even really need to strictly be "projects" but can be whatever you want
• Alyssa X, from whom I got the idea for video preview banners, although I opted to make them autoplay, instead of on mouseover, for mobile-friendliness
• Art Chaidarun, from whom I got the idea of masonry-style tiling, and I might potentially also do those cool stack filters

I began by adding the most important stuff for now, and might add some more over time. I keep pretty good notes of everything I do, so this list could become very very long, as I've worked on a lot of things over time. I realised that a few, cool, recent things are more meaningful than many, old, arbitrary things, so I'll try not to make this grid too large, and link to the full directory of projects (at least the ones that have made their way online) in the last tile.

It would have also been quite boring I think if I listed all my publications, as they're largely related. The same holds true for every weekend project, hackathon, game jam, utility script, game mod, etc. The projects I worked on during university I think are similarly just too old now. I also left out my volunteering work because it felt a bit too vain to include, and I'm not sure it would actually spur on any meaningful conversation. I also left out the things where I don't have significant enough involvement.

Please let me know your thoughts on the above and/or on how to improve this!

Some days ago, OpenAI released the code and models for Shap-E, which lets you do text-to-3D, and download a mesh you can use in any 3D software or for game development (rather than NeRFs with extra steps like previous models, and many papers that never released their code). This is very exciting, as the quality is reasonably good, and previously I would try to get that through various hacks.

There is already a HuggingFace space to try it, but no model on HuggingFace that you can easily use with their Inference API. You can fork the space and turn it into an API with some extra work, but I wasn't able to easily figure this out, and since running your own space is expensive anyway, I decided to take the easy way out and put a Flask server on top of OpenAI's existing code.

My server implementation is here. Since generating a new model only takes a couple seconds, I decided to design the interface as a "just-in-time" download link. You request /models/cat.ply, and if it's been generated before, it will download right away, but if not, then it's generated on the fly while the request is blocking.

I ran this on vast.ai, on an A10 instance, but I'm probably not going to keep it up for long as it's a bit expensive. I used the default pytorch image, and tweaked the config to expose the server on port 8081, which is a Docker port that vast.ai then maps to a port on the host. I added a proxy to that on my Model Compositor project which you can try here for free.

My Red Maple and Wisteria seeds haven't sprouted yet, but I was left with all this extra soil! So I decided that I ought to plant the other species too. The remaining seeds I have are for Black Pine, Cherry Blossom, and Japanese Cedar. This is what they look like respectively:

I only had three Cherry Blossom seeds, and unlike the Red Maple, I decided to only plant one seed in that pot. Besides that, I've largely only used half of the seeds I have of each species so far, and I'm thinking that even that is unnecessary, but let's see!

As I was soaking them for 48 hours, they kind of got mixed up a bit, and I had a bit of a challenge separating the Black Pine from the Cherry Blossom, but I think I got there in the end. To better keep track of everything, as I was really starting to forget which is which, I put in some little wooden sticks:

The soil had dried quite a bit, so I made it wetter, maybe even a little too wet, as it was soaking the cotton on the bottom and created some condensation on the plastic. I also used tap water, which I didn't do for the first two, as it's pretty hard / rich in calcium. For my tomato plant, the effects of this were soon obvious as calcium residue was visible on the top of the soil and edges of the soil where it meets the pot. I didn't want to have the same for these plants, but it should hopefully all be OK.

If you'd like to learn some more about each species, here are their sections in my little book:

So now we have 5 different pots stratifying -- let's see which sprout first!

Dolly 2.0, a recently released open-source LLM, is a big deal, but not because there's anything new or special about it, but rather specifically because it's legally airtight. Unlike the models that were fine-tuned based on the leaked LLaMA model (many of which Meta takes down), it's based on the EleutherAI pythia model family. The training data is CC licensed and was crowd-sourced from 5000 Databricks employees.

Since it's on Hugging Face Hub, you can use it with Langchain, and I expect that it will become the Stable Diffusion of LLMs. I think especially companies that legally can't send their data off to the US will flock to using Dolly.

I kind of like how there's still this theme of woolly hooved animals (in this case a sheep), but still a divergence from the LLaMA strain of models (llama, alpaca, vicuna). I don't like how it sounds too similar to "DALL-E 2" when spoken though.

My bonsai seeds have soaked for 48 hours and I'm ready to move on to the next step! The reveal: I picked Wisteria and Red Maple. They ticked all the right boxes for me as my first try.

The Wisteria seeds are the small ones and the Red Maple are the two big ones. I used half of the seeds that I had of each species.

I assembled the "Auto Irrigation Growing Pot" and tried to ignore the conflicting instructions. I think you're not meant to fill the reservoir with any water at all until after the Stratification step (which I'll explain in a sec), and it's ambiguous how deep the seeds should go beyond "same depth as the size" (the size of what, the seeds?), so I just used my best judgement.

It turns out that I actually have a lot of soil. I didn't even use up a full peat disc so far. I have three more pots, so I'm considering getting some more seedlings started in the meantime and increase the chances of success...

At any rate, I sowed the current seeds and sprinkled a tiny bit of water into the soil to keep it moist, as it had dried out a bit in the meantime. I don't think the instructions should have the soil bit as step 1 if you're then going to soak the seeds for 48 hours after that, it should really be the second step.

And now that they're sown, I put them in the fridge. In the fridge, the one on the left is the Red Maple (this is more of a note to myself -- I should label them really; there are little wooden sticks for that in the kit). Putting them in the fridge is the first part of the Stratification step, which is meant to simulate winter conditions, then spring, so that they can germinate as they would in nature.

I'll be checking on them every few days and keeping the soil damp. Hopefully in two or three weeks they will start sprouting and I can remove them from the fridge. I set some calendar events. So now we wait!

I'm in the process of organising a big pile of bookmarks, the current batch dating to 2019. I realised that while the ones from 2022 are still relevant, I really don't know why I bookmarked some of the things that I did in 2019. Some of them are kind of interesting articles, but I no longer remember what my intention was.

Was it to read them later? I think they're mostly just not that interesting to me anymore. Was it to do use them somehow or keep them as a resource? If so, I don't see how, as they've usually lost their relevance.

I have already noticed that the rate at which I bookmark links is much higher than the rate at which I triage them. Part of this is because the triage process is still too high-friction for me. Most of the time, I want to be able to very easily categorise and store a resource in the right place for later search, or append it to the scratch file of a relevant project.

I always knew that I need to take measures to ensure that the "service rate" of these lists is higher than the rate at which they grow, but now I also think that there's a certain time cutoff after which the lists might as well be self-pruning. After all, if something's been in the "backlog" for so long, surely it can't be that important? I need a Stale Bot for bookmarks!

I finally decided to start on my bonsai project. To read more about what this is all about, check out the project page. I haven't written anything about the tomato project, or any of the other (failed) horticulture projects, but I will eventually, since documenting failures is important too! This is the first log of what is probably going to be rather perennial chronicles.

The kit that I'm using to get a start with bonsai is really quite neat. It comes with 5 different species of seeds: Japanese Wisteria, Cherry Blossom, Japanese Cedar, Red Maple Tree, and Black Pine Tree.

This is a great set of tools in such a small package and I'm quite excited! The instruction booklet goes into a decent amount of detail, though I already know a bunch from YouTube and other places as I had a general interest in bonsai before deciding to try myself.

It came with two peat pucks that you put in some water and watch as they slowly grow while they absorb the water.

I decided to do both of them, as I wanted to try multiple species at the same time, and they grow to about 3x their original size! It's actually quite a lot of soil.

I then decided on two species that I wanted to grow. The next step was to put some of the seeds in warm water for 48 hours, such that they can soften, which makes it easier for the seedling to break through the shell. The two that I picked had seeds that looked very distinct from each other!

If you would like to know what species I picked, check back in 48 hours when I document the sowing process! I'll give you a hint: I didn't pick the mainstream choice (Black Pine).

A common way - if not the most common way (looking at WordPress dominance) - to do i18n is using the "Portable Object" format. You start off with a template file (.pot) and normally you would load that into Poedit, type in your translations for every string (including plurals), then download a pair of files: the .po and the "compiled" Machine Object .mo file.

Unfortunately, my daily driver is an arm64 device (my phone actually -- a lot of people think this is insane, but I'll write it up eventually and explain myself). I can't run Poedit without some crazy hacks. You could also copy the .pot file to a .po file, then just edit that directly (it's a straightforward text file), and there are some tools to convert .po to .mo, but that's all a bit of a hassle.

As luck would have it, there's a great free tool online that does everything I need called Loco. You load whatever file in, do your translations (with optional filtering), and download the files. You can save it to a cloud account (which is I think how they make money) but I had no need of that.

I figured this all out after being given access to a WordPress deployment to help an organisation out with some things. Previously, I only had access to the WP dashboard, and changed some text for them via CSS. Now that I had FTP access, I could just change everything in one fell swoop by modifying the English strings for the site, and I deleted the hacky CSS. Once you copy the files back over, everything is automatically updated.

A few days ago, I wrote a post where I reminisced about the online forums of yesteryear. I mention tracking down and reaching out to a webmaster of a forum that meant a lot to me. Well, I have an update: she responded, and it was indeed her! I considered asking her if she might be open to digging up any backups she might have had, but then I thought about it, and I figured that perhaps some things are better left in the past. I don't remember the contents of those posts, but I do remember the positive emotions, and I think that's enough.

This leads me onto a topic that I've wanted to write about for a while: data-hoarding. I personally struggle with the concept of entropy in general. This manifests itself in many ways, but a clear one is information loss. If I were to leave this unchecked, I could see myself easily becoming a data-hoarder. The impulse is much stronger for unique data that I created (personal data), and in fact this is probably a strong motivator for my note-taking, as I see writing as a form of "backing up my brain". I've barely scratched the surface, but I reckon with enough data, I could even be resurrectable.

In my personal notes, I have a directory called "maxims", where I reason about a set of principles that I live my life by. There are however a certain set of mental tools that help me cope with life in general, but aren't quite at the level of certainty of a "maxim". I decided to start writing these down, and for now I'm putting them in a separate folder called "meditations" (kind of inspired by Marcus Aurelius' writing) until I come up with a better name.

The reason I bring this up is because there's a useful tool that helps me mitigate this urge to hoard personal data, namely picturing the notion that, for all we know, physics seems to indicate that our universe is time-reversible (except when you're dealing with black holes, but let's not get into that). In other words, if you know the end state of a system, and its evolution laws, you can simulate it backwards and determine a previous state, regardless of how chaotic it may be. Of course, it's one thing to calculate where a thrown ball originated from, another to un-burn a book, but physically it's all the same.

Similarly, relativity seems to indicate that if you travel at the speed of light, then all of time can exist at once, bringing up the concept of a Block Universe, and our perception of past and present is more of a side-effect of our mode of existence. To that end, I like to imagine that if certain data has existed at some point, then it is "stored", and theoretically retrievable, in the past, or the Akashic Records to use the term I learned from Ra. If not through "time-travel", then if someone were to take a perfect snapshot of our universe and simulate physics in reverse.

If you find this kind of thing interesting, I recommend Sabine Hossenfelder's book "Existential Physics", which she signed for me after a talk at the Royal Institute!

Before I get too carried away, let me write down one more story. When I was little, we had a Win 98 computer. I knew that machine inside and out. I remember all the games I used to play on it with my brothers (anyone remember the Worms games?) and I remember making little games with the old versions of PowerPoint. We made a mouse-maze game at one point, called "The A-maze-ing Maze", and in my head I can still hear the voice-over recording that I asked my brother to make for the instruction slide of the game, and his inflection of the word "maze".

I kept it in good working condition probably until I went off to university. Some people are amazed at how well-kept my projects from the early 2000s are, but that computer truly had even the earliest projects I ever worked on on it.

My mother didn't like that I always had electronics and hardware lying around in my room. She often threatened to throw my things out. I told her that this old computer was especially important to me, and I put it in my closet so that it's not in the way.

At some point, I probably came back home from uni to visit, and the computer was gone. My mother told me that she had it scrapped, and it was long gone at that point. I can't remember how I reacted, but I often remember the feeling, and I'm not sure if I'll ever get over that loss, as silly as that may sound. It truly felt like losing a part of myself.

I have a good relationship with my mother, and I've brought this up several times since then, but I don't think she quite understands what it meant to me, and she never apologised. Usually, she says that she assumed that I had already pulled out the hard drive, as I had a very tall stack of what she assumed were hard drives (they were actually CD-ROM drives).

Anyway, I'm not writing this to roast my mum! In fact, allow me to add one more anecdote (I lied, sorry) to offset the above story somewhat. One of my earliest memories of losing progress that hadn't saved was when playing the game "Amazon Trail" (a somewhat more modern spin-off of the well-known Oregon Trail). I made hours of progress on that game, and lost everything to a crash. My mother was the one who was there to comfort me as I cried.

I'm sharing this to put into words a different kind of loss, and a means of managing it. Like with the death of a person, you can imagine that they exist on in your memories. I like to think that the things I lose exist in a much more concrete way, in space-time itself, and that the loss was deterministically inevitable.

While that might not yet enable me to let go of certain losses, I can at least avoid obsessing over hoarding other data, and allowing certain things to be forgotten. Perhaps that can help someone else too!

I need to make a new update post on all the AI stuff. Things move so fast that I often just can't be bothered! I'm making this post mostly for myself and people who ask about something very specific.

LangChain recently announced classes for creating custom agents (I think they had some standard Agents before that too though). Haystack has Agents too, although it seems that their definition explicitly involves looping until the output is deemed ok, as most implementations need to do this anyway.

The way I understand this and see it implemented is that it's essentially an abstraction that allows LLMs (or rather, a pipeline of LLM functions) to use "tools". A tool could for example be a calculator, a search engine, a webpage retriever, etc. The Agent has a prompt where it can reason about which tool it's supposed to use, actually use these, and make observations, which it can then output.

It also allows for the decomposition of a task and taking it step by step, which can make the system much more powerful. It's a lot closer to how a human might reason. An example of this general idea taken to the extreme is Auto-GPT which you can send on its merry way to achieve some high level goal for you and hope it doesn't cost you an arm and a leg. Anyone remember HustleGPT btw?

There's something called the ReAct framework (Reasoning + Acting -- I know, unfortunate name) which is the common "prompt engineering" part of this, and prompts using this framework are usually built in to these higher-level libraries like LangChain and Haystack. You might also see the acronym MRKL (Modular Reasoning, Knowledge and Language, pronounced "miracle") being used. This comes from this older paper (lol, last year is now "old"), and it seems that ReAct is basically a type of MRKL system that is also able to "reason". They might be used interchangeably though and people are often confused about where they differ. The ReAct paper has much clearer examples.

A common tool is now, of course, embeddings search, which you can then chain to completion / chat. You might remember two months ago when I said at the bottom of my post about GPT use cases that this is where I think the gold dust lies. Back then, I had linked gpt_index; it's now called llama_index and has become relatively popular. It lets you pick what models you want to use (including the OpenAI ones still, unlike what the rename might suggest), what vector store you want to use (including none at all if you don't have loads of data), and has a lot of useful functionality, like automatically chopping up PDFs for your embeddings.

Not too long ago, OpenAI released their own plugin for this, that has a lot of the same conveniences. One surprising thing: OpenAI's plugin supports milvus.io as a vector store (an open-source, self-hosted version of the managed pinecone.io) while llama_index doesn't. I don't think it's worth messing around with that though tbh, and I think pinecone has one of those one-click installers on the AWS marketplace. If you're using Supabase, they support the pgvector extension for PostgreSQL, so you can just store your embeddings there, but from what I hear, it's not as good.

Of course, if you're subject to EU data regulations, you're going to use llama_index rather than send your internal docs off to the US. I say internal docs, because it seems everyone and their mother is trying to enter the organisational knowledge retrieval/assistant SaaS space with this. Some even raising huge rounds, with no defensibility (not even first-mover advantage). It's legitimately blowing my mind, and hopefully we don't see a huge pendulum swing in AI as we did crypto. We probably will tbh.

The only defensibility that may make sense is if you have a data advantage. Data is the gold right now. A friend's company has financial data that is very difficult to get a hold of, and using llama_index, which is the perfect use. Another potential example: the UK government's business support hotline service is sitting on a treasure trove of chat data right now also. Wouldn't it be cool to have an actually really good AI business advisor at your beck and call? Turn that into an Agent tool, and that's more juice to just let it run the business for you outright. Accelerando autonomous corporation vibes, but I digress!

Personally, I would quite like an Obsidian plugin to help me draw connections between notes in my personal knowledge base, help me organise things, and generally allow me to have a conversation with my "memory". It's a matter of time!

Veronica recently sent me this puzzle:

In English: the grid is a city and you must place buildings in the cells. Buildings can have a height between 1 and 5 floors inclusive. Rows and columns have Sudoku rules; you can't have a building of the same height be on the same row/column. The numbers on the edges are how many buildings are visible from that vantage point.

So for example, for a row of 13254, the number on the right would be 2 (you can only see the buildings 4 and 5) and the number on the left would be 3 (you can only see 1, 3, and 5).

Give it a go then check against my solution!

When I was much younger, after the internet had already picked up mainstream steam, but before social media, I spent a lot of time on online forums. The communities were small (and even if they were big, the "regulars" were a small community) and everyone knew everyone. Most of these no longer exist and the chances that I can reconnect with the friends I made are very slim, which is a shame as they've strongly influenced who I am today. I hear that similar communities exist on Mastadon and in some pockets of the internet but I already know it just won't be the same.

I'd get home from school, sit at the family computer, and check for new posts in threads I was part of. For the smaller ones, I would check all new posts on the entire forum and I engaged in a lot of discussions. I remember runescape-tip.com with waves of nostalgia as I just looked it up on the Wayback Machine (we're talking mid-2000s). I also remember the mutual support between friends on teenforum.tv, under the administration of the 21 year old webmaster and MySpace-layout-maker Nora, who seemed so old and wise at the time. Some friendships survived the forums' demise, but somewhere between transitions from MSN to Skype and beyond, it all fizzled away.

One forum that survived to this day however is dreamviews.com, although it looks quite different to how I remembered it. In typical vBulletin fashion, every year I get a birthday email from there, and every year I remember the friends I made on there. We obviously spoke a lot about lucid dreaming, a topic I was very interested in (though barely had any), but also a lot of off-topic stuff. Judging by the length of time the emails go back, I was active on there "only" as far back as 2010, which is later than the others.

I remember checking DreamViews one day, a long time ago, after I had already been inactive for quite some time (probably as I was at uni and busy with life) and I saw a post with one of the more veteran users on the site, reminiscing about all the "old" active users that had gone inactive. He listed usernames that I recognised, and mine was among them! That was the first time I considered that I too might have had an impact on all these people who had an impact on me, and that I wasn't just a random internet stranger to them. By the time I saw that post, the veteran user had also already moved on, so I decided to leave it there, and preserve these memories in my journaling as best I could.

I once tracked Nora down on a different platform, in 2014 (6 years after teenforum.tv died) and she had responded, according to my email notifications. I don't know what that response was anymore, because even that different platform (some kind of design community) is now dead too. Today, I did some sleuthing, and tracked her down on LinkedIn. I messaged her 5 minutes ago, and who knows, maybe she still has a backup of those forums and I can reminisce over the conversations? If anything comes of it, I'll be sure to post!

I can't imagine I'm the first to try this, but new hobby acquired:

1. Go to the British Museum (other museums with statues will work too!)
2. Find broken statues
3. Take a photo
4. Erase the gaps (DALL-E 2 lets you upload and edit on the fly)
5. Write the name of the piece as the prompt, with the date
6. Use image inpainting to fill in the rest of the statue

I ran the ones below on the spot and it was quite fun. Before this, whenever I visited the British Museum (a few times a year), I didn't really give most of those statues a second glance.

An exercise for the reader (this one's interesting because they put a reference of what it could have look like if it were complete based on a different statue):

And another bust of good old Caesar (might be interesting as there's so much reference material, and it's so broken):

Try it and have fun! I'll try another batch the next time I go.

I wrote a short article about a trick for editing the text in HTML text nodes with only CSS. This is one of those articles where the goal is just to share something that I learned or discovered, that someone might benefit from, and the primary mode of finding this content is through a search engine.

It doesn't quite make sense for this to be an "article" in the way that I use that word (a long-form post bound in time that people follow/subscribe to) so I might eventually turn all these guide-type posts into wiki-notes, so they can exist as non-time-bound living documents.

I'm glad this wasn't me with deen.ai!

Via Instagram

For a long time I've been interested in the idea of creating a digital twin of yourself. I've tried this in the past with prompt completion trained on many years of my chat data, but it was always just a bit too inaccurate and hollow.

I also take a lot of notes, and have been taking more and more recently (a subset of these are public, like this post you're reading right now). I mentioned recently that I really think that prompt completion on top of embeddings is going to be a game-changer here.

You probably already know about prompt completion (you give it some text and it continues it like auto-complete on steroids) which underpins GPT-3, ChatGPT, etc. However, it turns out that a lot of people aren't familiar with embeddings. In a nutshell, you can turn blocks of text into high-dimensional vectors. You can then do interesting things in this vector space, for example find the distance between two vectors to reason about their similarity. CohereAI wrote an ELI5 thread about embeddings if you want to learn more.

None of this is particularly new -- you might remember StyleGAN some years ago which is what first really made this concept of a latent space really click for me, because it's so visual. You could generate a random vector that can get decoded to a random face or other random things, and you could "morph" between faces in this space by moving in this high-dimensional space. You could also find "directions" in this space (think PCA), to e.g. make a slider that increases your age when you move in that direction, while keeping other features relatively unchanging, or you could find the "femininity" direction and make someone masculine look more feminine, or a "smiling amount" direction, etc.

The equivalent of embedding text into a latent space is like when you have an image and you want to hill-climb to find a vector that generates the closest possible image to that (that you can then manipulate). I experimented with this using my profile picture (this was in August 2021, things have gotten much better since!):

Today, I discovered two new projects in this space. The first was specifically for using embeddings for search which is not that interesting but, to be fair, is what it's for. In the comments of that project on HackerNews, the second project was posted by its creator which goes a step further and puts a chat interface on top of the search, which is the exact approach I talked about before and think has a lot of potential!

Soon, I would like to be able to have a conversation with myself to organise my thoughts and maybe even engage in some self-therapy. If the conversational part of the pipeline was also fine-tuned on personal data, this could be the true starting point to creating digital twins that replace us and even outlive us!

Some weeks ago I built the "Muslim ChatGPT". From user feedback, I very quickly realised that this is one use case that absolutely won't work with generative AI. Thinking about it some more, I came to a soft conclusion that at the moment there are a set of use cases that are overall not well suited.

Verifiability

There's a class of computational problems with NP complexity. What this means is not important except that these are hard to solve but easy to verify. For example, it's hard to solve a Sudoku puzzle, but easy to check that it's correct.

Similarly, I think that there's a space of GPT use cases where the results can be verified with variable difficulty, and where having correct results is of variable importance. Here's an attempt to illustrate what some of these could be:

The top right here (high difficulty to verify, but important that the results are correct) is a "danger zone", and also where deen.ai lives. I think that as large language models become more reliable, the risks will be mitigated somewhat, but in general not enough, as they can still be confidently wrong.

In the bottom, the use cases are much less risky, because you can easily check them, but the product might still be pretty useless if the answers are consistently wrong. For example, we know that ChatGPT still tends to be pretty bad at maths and things that require multiple steps of thought, but crucially: we can tell.

The top left is kind of a weird area. I can't really think of use cases where the results are difficult to verify, but also you don't really care if they're super correct or not. The closest use case I could think of was just doing some exploratory research about a field you know nothing about, to make different parts of it more concrete, such that you can then go and google the right words to find out more from sources with high verifiability.

I think most viable use cases today live in the bottom and towards the left, but the most exciting use cases live in the top right.

Recall vs synthesis

Another important spectrum is when your use case relies on more on recall versus synthesis. Asking for the capital of France is recall, while generating a poem is synthesis. Generating a poem using the names of all cities in France is somewhere in between.

At the moment, LLMs are clearly better at synthesis than recall, and it makes sense when you consider how they work. Indeed, most of the downfalls come from when they're a bit too loose with making stuff up.

Personally, I think that recall use cases are very under-explored at the moment, and have a lot of potential. This contrast is painted quite well when comparing two recent posts on HN. The first is about someone who trained nanoGPT on their personal journal here and the output was not great. Similarly, Projects/amarbot used GPT-J fine-tuning and the results were also hit and miss.

The second uses GPT-3 Embeddings for searching a knowledge base, combined with completion to have a conversational interface with it here. This is brilliant! It solves the issues around needing the results to be as correct as possible, while still assisting you with them (e.g. if you wanted to ask for the nearest restaurants, they better actually exist)!

Somebody in the comments linked gpt_index so you can do this yourself, and I really think that this kind of architecture is the real magic dust that will revolutionise both search and discovery, and give search engines a run for their money.

Welp, looks like I'm a month late for the N-O-D-E Christmas Giveaway. You might be thinking "duh, Christmas is long gone", and I also found it weird that the deadline was the 31st of January, but it turns out that that was a mistake in the video and he corrected it in the comments.

Since I keep up with YouTube via RSS, I didn't see that comment until it was too late. I only thought to check again when my submission email bounced.

Oh well! At least it gave me a reason to finally write up my smart home setup! This also wasn't the first time that participating in N-O-D-E events really didn't work out for me -- in 2018 I participated in the N-O-D-E Secret Santa and sent some goodies over to the US, and really put some effort into it I remember. Unfortunately I never got anything back which was a little disappointing, but hey, maybe next time!

I've been planning to start this project for a while, as well as document the journey, but never really got around to it. I had a calendar reminder that tomorrow the N-O-D-E Christmas Giveaway closes, which finally gave me the kick in the butt needed to start this one! I also want to use this as an opportunity to create short-form videos on TikTok to learn more about it (in this case, documenting the journey). The project page is here.

Recently, people whose work I admire made me have to confront the "art not artist" dilemma once more. In this case, Nick Bostrom with racism, and Justin Roiland with domestic abuse.

Thinking about it, more generally, I guess it comes down to:

1. I can no longer consume a creator's work work without it being tainted by the context of their negative actions, so it became worse for me
2. I do not want to a give a voice/reach to their views by making them more famous
3. I do not want to do 2 indirectly by financially supporting them
4. More selfishly, I do not want to be associated with them or for people to think I support their views/actions by supporting their work
5. I do not wanting to signal to others that they can normalise these kinds of views, or behave a certain way, without consequences

However, it makes me think about the question: what if an AI were to be in a similar situation? Done something good and also done something bad. The current vibe seems to be that AI is a "tool" and "guns don't kill people, people kill people". But once you assign agency to AI, it starts opening up unexplored questions I think.

For example, what if you clone an AI state, one goes on to kill, the other goes on to save lives, in what way is the other liable? It's a bit like the entanglement experiment that won the 2022 Nobel physics prize -- you're entangling across space (two forks of a mind) vs time (old "good" version of a celebrity vs new "bad" version of a celebrity) where all versions are equally capable of bad in theory. To what extent are versions of people connected, and their potential?

It also reminds me of the sci-fi story Accelerando by Charles Stross (which I recommend, and you can read online for free here) where different forks of humans can be liable for debts incurred by their forks.

On a related note, I was recently reading a section in Existential Physics by Sabine Hossenfelder titled "Free Will and Morals". Forgive the awful photos, but give it a read:

So it doesn't even have to be AI. If someone is criminally insane, they are no longer agents responsible for their own actions, but rather chaotic systems to be managed, just like you don't "blame" the weather for being bad, or a small child for making mistakes.

Then, what if in a sufficiently advanced society we could simply alter our memories or reprogram criminal intent away? Are we killing the undesirable version? The main reasons for punishment are retribution, incapacitation, deterrence, and rehabilitation, but is there research out there that has really thought about how this applies to AI?

There's a fifth reason that applies only to AI: Roko's Basilisk (warning: infohazard) but it's all connected, as I wonder what majority beliefs we hold today that future cultures will find morally reprehensible. It might be things like consuming animals or the treatment of non-human intelligence that is equivalent to or greater than humans by some metric. At least we can say that racism and domestic violence are pretty obviously bad though.

Twilio used to be a cool and trustworthy company. I remember when I was in uni, some CS students (I was not a CS student) built little SMS conversation trees like it was nothing, and suddenly SMS become something you could build things with as a hobby.

Over the past month, my view of Twilio has completely changed.

The attack

Ten days ago (Jan 19th) at around 7am UTC, I woke up to large charges to our business account from Twilio, as well as a series of auto-recharge emails and finally an account suspension email. These charges happened in the span of 3 minutes just before 5am UTC. My reaction at this point was confusion. We were part of Twilio's startup programme and I didn't expect any of our usage to surpass our startup credits at this stage.

I checked the Twilio dashboard and saw that there was a large influx of OTP verification requests from Myanmar numbers that were clearly automated. I could tell that they're automated because they came basically all at once, and mostly from the same IP address (in Palestine). At this point, I realised it was an attack. I could also see that this was some kind of app automation (rather than spamming the underlying API endpoint) as we were also getting app navigation events.

After we were suspended, the verifications failed, so the attack stopped. The attacker seemed to have manually tried a California IP after that some hours later, probably to check if they've been IP blocked, and it probably wasn't a physical phone (Android 7). Then they stopped.

I also saw that our account balance was more than £1.5k in the red (in addition to the charges to our bank account) and our account was suspended until we zero that balance. The timing could not have been worse as we were scheduled to have an important pitch to partners at a tier 1 VC firm. They could be trying the app out already and unable to get in as phone verification was confirmed broken.

Our response

We're on the lowest tier (as a startup) which means our support is limited to email. I immediately opened a ticket to inform Twilio that we were victims of a clear attack, and to ask Twilio for help in blocking these area codes, as we needed our account to be un-suspended ASAP. They took quite a long time to respond, so after some hours I went ahead and paid off the £1.5k balance in order for our account to be un-suspended, with the hope that they can refund us later.

I was scratching my head at what the possible motive of such an attack could be. I thought it must be denial of service, but couldn't think of a motive. We're not big enough for competitors to want to sabotage us, so I was expecting an email at any point from someone asking for bitcoin to stop attacking us, or a dodgy security company coming in and asking for money to prevent it. But Twilio sent an email saying that this is a case of toll fraud.

I recommend reading that article, but in essence, those numbers are premium numbers owned by the attacker, and every time Twilio sends them a verification SMS, they make money, and we foot the bill.

Twilio's response

Twilio seemed to follow a set playbook that they use for these situations. Their documentation names a set of countries as the one where toll fraud numbers most likely come from and recommend are blocked (I suppose it's easy to get premium numbers there): Bangladesh, Sri-Lanka, Myanmar, Pakistan, Uzbekistan, Azerbaijan, Kyrgyzstan, and Nigeria.

I immediately went and blocked those area codes from our side, though Twilio also automatically blocked all countries except the US and the UK anyway, so it didn't really make a difference. Also, the attacker tried again using Indonesian numbers after that, so clearly a blocklist like that is not enough. Later I went and one by one selectively allowed only countries we actually serve.

Beyond this, Twilio's response was to try and do everything to blame this on us. They wash their hands of the responsibility to secure their own APIs, and instead the onus is on us to implement our own unreasonable security measures.

I told a friend about this, and through that friend found out that this is actually a very common problem that people have been having with Twilio, because Twilio dropped the ball. Apparently, out of all of those cases, we got pretty lucky (some people lost 6 figures). For me, the main issues are:

• Why aren't risky countries blocked by default? Worse, why are all countries in the world allowed by default?
• Why isn't "Fraud Guard", one of the switches (free) that Twilio told us we should have turned on, already turned by default?
• I had set up an auto-recharge rule (charge to £20 if balance goes below £10) just in case the startup credits ever ran low. This backfired dramatically as the account kept auto-recharging in an infinite loop until we were suspended (the reason for the huge charges to our bank account). Why?!
• We were already using the default rate-limiting that applies to individual numbers (something like 5 verification requests every 10 minutes), and our server had some general global rate-limiting per-IP (this probably already protected us quite a bit from what could have been). How is it reasonable to expect your clients to put a global rate limit, across IPs and numbers, for specifically the endpoint that asks for Twilio verification? Just have the rate limit on your side maybe? It's not our responsibility to think of these kinds of things; that's why we're using third party provider!

Their email was incredibly patronising, like others have reported, and they acted like they're doing us a huge favour by blessing us with a partial refund in account credits (not even real money). But we need to explain to them first how we promise to be better and not do a silly mistake like this again!

The refund

Twilio tries to push you into agreeing not to dispute the bank charges (see the link above for why they do this). I refused to agree to this, and first wanted to know exactly how much they would refund us, and if they would refund us in real money, not account credits (they agreed to "prioritize" this).

They told us that their finance team is who decides the refund amount, based on the information we provide on how we'll do better and a breakdown of the charges. I told them exactly what we did to combat this, and what the charges were. We had lost a few hundred in startup credits, then just over £2k in real money.

Instead of telling me how much they would refund (remember, I still haven't agreed not to dispute the charges, which they "required" in order to issue a refund), they went ahead and refunded us £847 and some change immediately.

I believe this to be a ploy to try and prevent us from disputing the original charges, because if we dispute now, we would have more back than what they charged.

What now?

I sought some advice, with mixed opinions, but it seems quite clear that if we dispute these charges, at the very least it would mean that we can no longer use Twilio for SMS anymore (which I don't want to anyway). But, this means switching to a different provider before disputing.

It would be relatively easy to switch, as they all tend to work the same way anyway, but would still require:

• Researching other providers (that don't use Twilio in the backend)
• Reading their documentation
• Swapping out the libraries and a dozen or so lines of code
• Making sure we leave no room for another round of toll fraud
• Testing and deploying

This is not difficult, but time and effort that I don't have right now, as well as a distraction from our actual core product. I don't know if £1.1k is worth that "labour", or any extra stress that may come if Twilio decides to make a stink about this and pass us on to collections etc.

All I know is: Twilio, never again. I will advise people to not use Twilio for the rest of my life and longer depending on how that advice may spread and how long this article survives.

My brother's in New York and I was reminded of a scam we fell for there once. This wasn't the typical Time's Square Elmo-league stuff, but seemed quite legitimate! I wanted to recount the story in case it might help someone.

We were planning to visit the Empire State building (which by the way, wasn't that great, especially that foggy day) and when we arrived there we were shocked to see a queue going all around the block and across several streets. We were approached by a man named DeShawn Cassidy selling the New York Pass.

"You can leave. Your Wallet. At home," he says. "You can laugh at aaaaall these people," as he points to the massive queue, telling us we can skip it with the glorious New York Pass. It's fast-lane entry and cheaper tickets into the Empire State building and a bunch of other attractions around New York within a certain time period.

He was a very convincing and charismatic salesman. We asked him why the people in the queue aren't cleaning him out if it's so good. He threw his hands up and said, "It behooves me!" misunderstanding what that word means.

We paid him $80 for 5 passes I believe, which was a great deal. He rubbed his hands like a fly about to have a meal as we were taking the money out, and gave us a receipt, staking his name and reputation on it, "DeShawn Cassidy", and that we can call him at any time if we need anything.

Of course, you know how the rest of the story goes. DeShawn was all but erased from existence, and we didn't have the opportunity to "laugh at all these people" as the security made us queue like everyone else. The special entrances were only for people who actually worked in the building.

We thought that maybe there's a faster queue inside, after clearing the building queue, and at least we don't need to get new tickets. Wrong again! The man at the till took one look at our little plastic cards, and in the strongest New York accent that still rings in my mind to this day, said the infamous words:

New York Pass? Don't do nothin'!

Yesterday and today I've been tinkering at a new feature for this website that will allow others to edit my content in a seamless way! Some of my pages are now wikis, for example this one. Full write-up here with a surprise at the end!

Yesterday evening I had a call with three founders looking for some advice on specific things. Something that came up was how to make a proper pitch deck. My advice is usually to go to Slidebean and check out the pitch decks of some well-known companies. There's a clear pattern to how these are structured, depending on who the target of the deck is.

But recently, a different founder sent me a pitch deck asking for feedback and he used a platform called Tome^[1], and his slides were pretty cool, and when viewed on that platform could even have little video bubbles where he explains the slide. At first I though this was a GPT-3-based slide generator (similar to ChatBA (formerly ChatBCG)) but it seems to be more than that and looks like it could be a great tool for putting together a pitch deck on a whim!

Great article on some ways to interact with ChatGPT: https://oneusefulthing.substack.com/p/how-to-use-chatgpt-to-boost-your. I find it funny that so many people speak to ChatGPT politely (I do too). I wonder if post-singularity we'll be looked upon more favourably than the impolite humans.

Last weekend I built a small AI product: https://deen.ai. Over the course of the week I've been gathering feedback from friends and family (Muslim and non-Muslim). In the process I learned a bunch and made things that will be quite useful for future projects too. More info here!

A while ago I dug into my DNA via a number of services. I had the uncommon opportunity of being able to compare the results of two services (while only really paying for one). Now I finally got around to writing this up and might update it over time as I do more genealogy-related things. https://yousefamar.com/memo/notes/my/dna/

In my previous post I made a little block diagram. Here's the workflow for how I did that: https://yousefamar.com/memo/articles/writing/graphviz/

If you happen to have checked my main feed page in the past few days, you might have notice I've added a box to subscribe to a newsletter. This is meant to be a weekly digest of the posts I make the week before, delivered to your email inbox.

I think I'm getting close to figuring out a good system for content pipelines, though I still think about it a lot. As such, this newsletter part will mostly be an experiment for now. It won't be an automated email that summarises my posts, but rather I'm going to write it myself to begin with. I'd like to follow a style like the TLDR newsletter, which I've been following since they launched. This means e.g. a summary of cool products I might have bookmarked throughout the week, which might also give me the opportunity/excuse to review and organise them.

I'm not convinced that the medium of newsletters is the right way to consume content. I for one am a religious user of kill-the-newsletter to turn newsletters into Atom feeds. A lot of people consume content via their email inboxes though, and it seems easier to go from that to the feed format, rather than the other way around at the moment. At any rate, I want to create these various ways of consuming content. The pipeline for this content might look like this:

The other consideration is visibility of my audience. I don't actually know if anyone reads what I write unless they tell me (hi James!), and unless I put tracking pixels and such in my posts, but is it really that important? With email, you have a list of subscribers, which probably gives you slightly more data over feed readers polling for updates to your feed, but again, I don't really want to be responsible for a list of emails, and I don't like being at the mercy of the big email providers' spam filters if I want to send email from my own domain (yes, this is despite SPF/DKIM and all that, based on some voodoo you can still reach people's junk folder).

So I'm thinking for now I probably don't even really care who reads what I write, and if it becomes relevant (e.g. if I want to find out what people would like to see more of), I can publish a poll.

Not too long ago I mentioned that the search engines will need to add ChatGPT-like functionality in order to stay relevant, that there's already a browser extension that does this for Google, and that Google has declared code red. Right on schedule, yesterday Microsoft announced that they're adding ChatGPT to Bing. (If you're not aware, Microsoft is a 10-figure investor in OpenAI, and OpenAI has granted an exclusive license to Microsoft, but let's not get into how "open" OpenAI is).

I heard about this via this HackerNews post and someone in the comments (can't find it now) was saying that this will kill original content as we know it because traffic won't go to people's websites anymore. After all, why click through to websites, all with different UIs and trackers and ads, when the chat bot can just give you the answers you're looking for as it's already scraped all that content. To be honest, if this were the case, I'm not so sure if it's such a bad thing. Let me explain!

First of all, have you seen the first page of Google these days? It's all listicles, content marketing, and SEO hacks. I was not surprised to hear that more and more people use TikTok as a search engine. I personally add "site:reddit.com" to my searches when I'm trying to compare products for example, to try and get some kind of real human opinions, but even that might not be viable soon. You just can't easily find what you need anymore these days without wading through ads and spam.

Monetising content through ads never really seemed like the correct approach to me (and I'm not just saying that as a consistent user of extensions that block ads and skip sponsored segments in YouTube videos). It reminds me a lot of The Fable of the Dragon-Tyrant. I recommend reading it as it's a useful metaphor, and here's why it reminds me (skip the rest of this paragraph if you don't want spoilers): there's a dragon that needs to be fed humans or it would kill everyone. Entire industries spring up around the efficient feeding of the dragon. When humans finally figured out how to kill it, there was huge resistance, as among other things, "[t]he dragon-administration provided many jobs that would be lost if the dragon was slaughtered".

I feel like content creators should not have to rely on ads in the first place in order to be able to create that content. I couldn't tell you what the ideal model is, but I really prefer the Patreon kind of model, which goes back to the ancient world through art patronage. While this doesn't make as much money as ads, I feel like there will come a point where creating content and expressing yourself is so much easier/cheaper/faster than it is today, that you won't have high costs to maintain it on average (just look at TikTok). From the other side, I feel like discovery will become so smooth and accurate, that all you need to do is create something genuinely in demand and it will be discovered on its own, without trying to employ growth hacks and shouting louder than others. I think this will have the effect that attention will not be such a fiery commodity. People will create art primarily for the sake of art, and not to make money. Companies will create good products, rather than try to market worthless cruft. At least that's my ideal world.

So how does ChatGPT as a search engine affect this? I would say that this should not affect any kinds of social communication. I don't just mean social media, but also a large subset of blogs and similar. I think people will continue to want to follow other people, even the Twitter influencer that posts business tips, rather than ask ChatGPT "give me the top 5 business tips". I believe this for one important reason: search and discovery are two different things. With search, there is intent: I know what I don't know, and I'm trying to find out. With discovery, there isn't: I don't know what I don't know, but I loiter in places where things I would find interesting might appear, and stumble upon them by chance.

Then there's the big question of having a "knowledge engine" skipping the sources. Let's ignore the problem of inaccurate information^[1] for now. I would say that disseminating knowledge at the moment is an unsolved problem, even through peer-reviewed, scientific journal papers and conference proceedings (this is a whole different topic that I might write about some day, but I don't think it's a controversial view that peer-review and scientific publishing is very, very broken).

I do not believe that the inability to trace the source of a certain bit of knowledge is necessarily the problem. I also don't believe that it's necessarily impossible, but lets pretend that it is. It would be very silly I think to cite ChatGPT for some fact. I would bet that you could actually get a list of references to any argument you like ("Hey ChatGPT, give me 10 journal citations that climate change is not man-made").

I think the biggest use cases of ChatGPT will be to search for narrowly defined information ("what is the ffmpeg command to scale a video to 16:9?") and discover information and vocabulary on topics that you know little about in order to get a broad overview of a certain landscape.

However, I don't see ChatGPT-powered search killing informative articles written by humans. I see AI-generated articles killing articles generated by humans. "Killing" in the sense that they will be very difficult to find. And hey, if ChatGPT could actually do serious research, making novel contributions to the state-of-the-art, while citing prior work, then why shouldn't that work be of equal or greater value to the human equivalent?

In the case of AI-generated garbage drowning out good human articles just by sheer quantity though, what's the solution? I think there are a number of things that would help:

1. Being able to trace sources and build trust metrics for specific sources. The consumer of the content of course wouldn't want to check every source, but they can trust that the reputable journalist or tech reviewer did their due diligence.
2. Collaborative curation: wikis (and Wikipedia itself) having transparent and well-enforced moderation. ChatGPT can be trained on this information, but if a concept surfaces in a chat, it can always be looked up in this structured repository of information. This will ideally be as objective as possible, so where you would have usually looked at a "Jira vs Linear" article and wonder which one of those two organisations wrote it, a lot more energy will be aimed at these "comparison of project management software" tables on Wikipedia, with a higher degree of accountability.
3. For things that aren't general knowledge (e.g. let's say you wanted to document a personal project), to have some set standards in order to contribute this information to a bigger collection of federated knowledge. No, I'm not just reinventing the internet, think more of a federated wiki that's marked up and structured in such a way that indexing/search is much less data-miney and prone to SEO tricks. A truly collaborative digital garden.

Overall I think that ChatGPT as the default means of finding information is a net positive thing and may kill business models that were flawed from the start, making way for something better.

I finally wrote an article on my thoughts about ChatGPT after a lot of repeated questions/answers from/to people: https://yousefamar.com/memo/articles/ai/chatgpt/

This is one of those things where I'm not sure it should really be an "article" but instead something more akin to a living document that I update continuously, maybe with a chronological log included. At the same time, a lot of the content is temporally bound and will probably lose relevance quite fast. Something to figure out in the future!

Amarbot was using GPT-J (fine-tuned on my chat history) in order to talk like me. It's not easy to do this if you follow the instructions in the main repo, plus you need a beefy GPU. I managed to do my training in the cloud for quite cheap using Forefront. I had a few issues (some billing-related, some privacy-related) but it seems to be a small startup, and the founder himself helped me resolve these issues on Discord. As far as I could see, this was the cheapest and easiest way out there to train GPT-J models.

Unfortunately, they're shutting down.

As of today, their APIs are still running, but the founder says they're winding down as soon as they send all customers their requested checkpoints (still waiting for mine). This means Amarbot might not have AI responses for a while soon, until I find a different way to run the model.

As for fine-tuning, there no longer seems to be an easy way to do this (unless Forefront open sources their code, which they might, but even then someone has to host it). maybe#6742 on Discord has made a colab notebook that fine-tunes GPT-J in 8-bit and kindly sent it to me.

I've always thought that serverless GPUs would be the holy grail of the whole microservices paradigm, and it might be close, but hopefully that would make fine-tuning easy and accessible again.

My friend Selvan sent me this puzzle:

Feel free to give it a try before revealing my thought process and solution! Also, in case you're wondering, the sticks do have to have marshmallows on both ends, and they're straight, and marshmallows can't be in the same position or at infinity. Also, the sticks can cross (this doesn't violate the "2D" requirement). None of this was obvious to me!

Obsidian Canvas was released today and I find this very exciting! As you might know, I'm a very visual thinker and try to organise my thoughts in ways that are more intuitive to me. I've always thought that an infinite canvas that you can place nested collapsible components and primitives on makes much more sense than a directory tree. I've used other tools for this, but the separation from my PKM tool (Obsidian) has always been a big barrier.

Obsidian keeps getting better over time! It seems the canvas format is relatively simple, where I reckon I could have these be publishable. More importantly though, I think it would be quite useful to organise my thoughts internally. Currently I use a combination of whiteboard wallpaper, actual paper, and Samsung Notes on my S22 Ultra; the only not-bad Android note-taking app with good stylus support, but frustratingly it doesn't let you scroll the page infinitely in the horizontal direction!

It can be a bit frustrating to try and manipulate a canvas without over-reliance on a mouse, but I don't think there are any ergonomic ways to interact well with these besides a touch screen, and at least the keyboard shortcuts for Canvas seem good. When AR becomes low-friction, I hope to very soon be able to use 3D spaces to organise documents and assets, in a true mind palace. For now, Obsidian Canvas will do nicely though!

/u/dismantlemars created a colab to run OpenAI's new Point-E model that you can use here. My first few experiments were interesting though not very usable yet! Supposedly it's thousands of times faster than DreamFusion though (the most well known crack at this). It took me about 30 secs to generate models, and converting the point cloud to a mesh was instant.

I tried to first turn my profile picture into 3D, which came out all Cronenberg'd. To be fair, the example images are all really clean renderings of 3D models, rather than a headshot of a human.

Then I tried the text prompt "a pink unicorn" which came out as an uninteresting pink blob vaguely in the shape of a rocking horse. Simply "unicorn" looked a bit more like a little dinosaur.

And finally, "horse" looked like a goat-like horse in the end.

The repo does say that the text to point cloud model, compared to the image to point cloud model is "small, worse quality [...]. This model's capabilities are limited, but it does understand some simple categories and colors."

I still find it very exciting that this is even possible in the first place. Probably less than a year ago, I spoke to the anything.world team, and truly AI-generated models seemed so far out of reach. Now I feel like it won't be much longer before we can populate entire virtual worlds just by speaking!

On a related note, I recommend that you join the Luma waitlist for an API over DreamFusion.

There are APIs out there for translating natural language to actions that a machine can take. An example from wit.ai is the IoT thermostat use case.

But why not instead use GPT-3? It ought to be quite good at this. And as I suspected, the results were quite good! The green highlighted text is AI-generated (so were the closing braces, but for some reason it didn't highlight those).

I think there's a lot here that can be expanded! E.g. you could define a schema beforehand rather than just give it some examples like I have, but I quite like this test-driven approach of defining what I actually want.

I did some tweaks to teach it that I want it to put words in my mouth as it were. It invented a new intent that I hadn't defined, so it would probably be useful to define an array of valid intents at the top. It did however manage to sweet-talk my "wife"!

I think this could work quite well in conjunction with other "modules", e.g. a prompt that takes a recipient, and a list of people I know (and what their relationship is to me), and outputs a phone number for example.

Amazon's creating AI-generated animated bedtime stories (story arc, images, and accompanying music) with customisable setting, tone, characters, and score. I believe that procedurally generated virtual worlds will be one of the prime use cases for these large models, and this is one example that I expect to see more of!

https://www.zdnet.com/home-and-office/home-entertainment/amazons-create-with-alexa-highlights-the-intersection-of-ai-and-creativity/

I think the most difficult part here will be to craft truly compelling and engaging stories, though this is probably soon to be solved. My brother and I attempted a similar project (AI-generated children's books) and the quality overall was not good enough at the time, but at the speed these things move I expect that to be a thing of the past in a matter of months!

Yesterday GitHub Copilot engineers borked production and I felt like someone had suddenly turned the lights off.

I hadn't realised how accustomed I had become to using it until this happened. I would make my intent clear in the code, then wait for it to do its thing, then it just wouldn't. Y'all got any more of them AIs?

At the same time, the next time you deploy a bad build to production, remember that even the big guys do it!

I wrote an article on bruteforcing Tailscale domain names (code included!): https://yousefamar.com/memo/articles/hacks/tailnet-name/

I'm letting day-nft.com expire. This was an experiment with 3 other people where we minted simple NFTs that each correspond to a different date going back something like 10 years. The technical part was relatively straightforward, but we realised that the whole thing is just one big hype game, and in order for it to succeed we would need to do things that we weren't comfortable with morally, so we abandoned the project. At that point I had already done some research and analysis on NFT marketplaces (which I intent to publish at some point) that helped me cement the current views I hold about this space.

Seems like GPT-4 is just around the corner! I'm really looking forward to it and not just the improvement on GPT-3, but the multi-modal inputs. I really think GPT-4 and models like it will be central to our future.

Nvidia's new diffusion model is really pushing the envelope. A lot of exciting capabilities!

I'm certain the market for GPT3-based spreadsheet plugins/add-ons is ripe for sales much more than libraries that target developers like cerebrate.ai. I've seen a general-purpose add-on for Google Sheets here, but I think that crafting these prompts to do specific things and wrapping these in higher-level functions has much more potential.

More Stable Diffusion resource links: https://rentry.org/sdupdates2

It's official — Amarbot has his own number. I did this because I was using him to send some monitoring messages to WhatsApp group chats, but since it was through my personal account, it would mark everything before those messages as read, even though I hadn't actually read them.

My phone allows me to have several separate instances of WhatsApp out of the box, so all I needed was another number. I went for Fanytel to get a virtual number and set up a second WhatsApp bridge for Matrix. Then I also put my profile picture through Stable Diffusion a few times to make him his own profile picture, and presto: Amarbot now has his own number!

In case the profile picture is not clear enough, the status message also says that he's not real. I have notifications turned off for this number, so if you interact with him, don't expect a human to ever reply!

Some of my HNS domains are expiring soon and I don't think I'll renew them. While the concept is super cool, unless Chrome and Safari adopt HNS, it'll never go anywhere. I now think it's very unlikely that they ever will.

I wrote an article on Y Combinator and the drama with DreamWorld: https://yousefamar.com/memo/articles/entrepreneurship/y-combinator/

Almost exactly 6 years ago, I ate too many Pringles, as reminded by my photo app throwback. My brother won a contest where the prize was crates of Pringles and he gave me all the sour cream and onion ones. I ate too many of them in too short a time and since then I kind of lost my taste for them. The same thing happened to me with peanuts — I used to love them and now I basically never eat them.

When I was a student, I got an oyster photocard for commuting with a discount. Eventually I also had my railcard added to this (though IIRC, the discounts aren't cumulative). I had it renewed right at the last possible moment before expiry and aging out, and the new card was meant to expire on the 31st of Jan 2020. It never did and I've been using it since — maybe expiry meant the discount?

Eventually the outermost plastic layers peeled off (the layer with my name and photo on it) leaving an ominous blank card.

The card number was also peeled off, so when I had an incomplete trip one day, while getting that sorted, a friendly TFL employee let me know what it was on a receipt of my past few journeys. Only then did I really think about what the point of using an oyster card is (since I'm not getting discounts anymore) over a contactless credit card.

It seems there isn't really much of a benefit for me, so I'll probably just let it run out and stop using it. I might draw a little picture in that empty spot.

I had a normal oyster card many many years ago (before the first photocard) that I at some point added to the online dashboard with 60p still on it. I had given this oyster card to a homeless lady thinking there was more than that on it and she probably tossed it. I reckon if I plan my last trip in such a way that the balance goes to -60p, then never top it up again, then my overall balance with TFL should be... well, balanced!

Hello twitter! This post was syndicated using Bridgy.

https://www.vice.com/en/article/jgpb3p/this-danish-political-party-is-led-by-an-ai

As of today, if you react to a message you send me on WhatsApp with a robot emoji (🤖), Amarbot will respond instead of me. As people in the past have complained about not knowing when I'm me and when I'm a bot, I added a very clear disclaimer to the bottom of all bot messages. This is also so I can filter them out later if/when I want to retrain the model (similar to how DALL-E 2 has the little rainbow watermark).

The reason I was able to get this to work quite easily is thanks to my existing Node-RED setup. I'll talk more about this in the future, but essentially I have my WhatsApp connected to Matrix, and Node-RED also connected to Matrix. I watch for message reactions but because those events don't tell you what the actual text of the message is that was reacted to was, only the ID, I store a small window of past messages to check against. Then I query the Amarbot worker with the body of that message and format and respond with the reply.

This integrates quite seamlessly with other existing logic I had, like what happens if you ask me to tell you a joke!

Amarbot has been trained on the entirety of my WhatsApp chat logs since the beginning of 2016, which I think is when I first installed it. There are a handful of days of logs missing here and there as I've had mishaps with backing up and moving to new phones. It was challenging to extract my chat logs from my phone, so I wrote an article about this.

This is my first post! More info here.