Archive

C3 programming language. Full C ABI compatibility, Module system, Generic modules, Design by contract, Zero overhead errors, Semantic macro system, First-class SIMD vector types, Struct subtyping, Safe array access using slices, Easy to use inline assembly, Cross-platform standard library which includes dynamic containers and strings, LLVM backend.

C3 Tutorial; has online playground.

C3 Blog by the creator, Christoffer Lernö

Also look at dlang's betterC - Better C - D Programming Language

llama homepage The latest, as on Jul 2024, is llama 3.1 which has 405B, 70B and 8B models, optimized for "do it all", cost/performance tradeoff, and light-weight+speed.

You can run llama locally on your laptop or pc using the following tools:

1. ollama + OpenWebUI;
   1. ollama is an open-source project that provides an easy way to download and run local LLMs
   2. OpenWebUI gives you a web-based ChatGPT like user interface to interact with the local LLMs.
2. LM Studio - is a desktop app
3. GPT4All is an open-source ecosystem for running LLMs locally on your computer.
4. MLX; optimized to run LLMs on Apple Silicon on macOS.

[via](https://x.com/shrihacker/status/1838996780236812638)

[@10.14778/3611479.3611527]; PDF

We argue that the disruptive influence that LLMs will have on data management will come from two angles. (1) A number of hard database problems, namely, entity resolution, schema matching, data discovery, and query synthesis, hit a ceiling of automation because the system does not fully understand the semantics of the underlying data. Based on large training corpora of natural language, structured data, and code, LLMs have an unprece- dented ability to ground database tuples, schemas, and queries in real-world concepts. We will provide examples of how LLMs may completely change our approaches to these problems. (2) LLMs blur the line between predictive models and information retrieval systems with their ability to answer questions. We will present examples showing how large databases and information retrieval systems have complementary functionality.

(Shi et al. 2024)

writing SQL queries requires specialized knowledge, which poses a challenge for non-professional users trying to access and query databases. Text-to-SQL parsing solves this issue by converting natural language queries into SQL queries, thus making database access more accessible for non-expert users. To take advantage of the recent developments in Large Language Models (LLMs), a range of new methods have emerged, with a primary focus on prompt engineering and fine-tuning. This survey provides a comprehensive overview of LLMs in text-to-SQL tasks, discussing benchmark datasets, prompt engineering, fine-tuning methods, and future research directions.

References

• Shi, Tang, Yang (2024). A Survey on Employing Large Language Models for Text-to-SQL Tasks.

Apache Pinot™ -- "The real-time analytics open source platform for lightning-fast insights, effortless scaling, and cost-effective data-driven decisions."

What is Apache Pinot? | Apache Pinot 101 - YouTube by Tim Berglund. latency, concurrency, freshness.

15 Years of Realtime OLAP (Part 1) - by Chris Riccomini

Pinot used columnar storage and in-memory buffering. But they also included a new feature: star-tree indexes. Star-trees give operators a knob to tune, trading off space for query latency. Though data was stored in columnar files as with Druid, for very fast (single-digit millisecond) reads, data could be partially pre-materialized. Pinot became widely adopted within LinkedIn and Uber for internal business intelligence, user-facing analytics features, log analytics, metrics, and more.

Keynote: Kishore Gopalakrishna (CEO, StarTree) Mission Critical Data Can't Wait | RTA Summit '24 - YouTube

Wes McKinney - The Road to Composable Data Systems: Thoughts on the Last 15 Years and the Future; (Pedreira et al. 2023) PDF

The stack proposed by this article:

• apache-arrow -- language-independent compute and data interchange layer and supporting systems infrastructure across important programming languages
• ibis and dplyr --  backend-agnostic data frame interfaces
• RAPIDS -- GPU-accelerated libraries for data analytics and machine learning
• duckdb and velox --  embeddable systems providing fast columnar query processing
• Substrait -- - language-independent intermediate representation (IR) middleware for analytical computing to assist in decoupling user interfaces from compute engines

References

• Pedreira, Erling, Karanasos, Schneider, McKinney, Valluri, Zait, Nadeau (2023). The Composable Data Management System Manifesto.

Homepage: Quarto.

If you are using pandoc to publish stuff, quarto might be a better wrapper for "books". My interest was re-piqued because now they also support typst. In addition:

Quarto includes native support for Observable JS, a set of JavaScript enhancements created by Mike Bostock (the author of D3). Observable JS uses a reactive execution model, and is especially well suited for interactive data exploration and analysis.

You can email me at pradeep🌀btbytes.com.

---

More often than not, I choose btbytes as the username on any web services I use.

• github
• linkedin
• twitter
• exercism (coding exercises)
• filtra
• hacker rank
• ORCID is 0000-0002-3906-1041

generative art is made by a process that has some level of autonomy. The role of the artist is to design or influence this process to some degree. This process can be any number of things, and as such it is not limited to the digital realm. It can just as easily be a system driven by a chemical reaction. Or a set of rules for coloring in a checkered sheet of paper. viano

• Schotter - Georg Nees
• Anifusion.ai -- infinite canvas UI for generative AI art.
• Generative art by Anders Hoff · inconvergent

Pretty much all major languages compile[^1] to Javascript .. so this is no longer an exclusive category. This page is an attempt to capture slightly offbeat/interesting languages that do. You may also be intereste din wasm, javascript.

--

Wasp "Rails-like framework for React, Node.js and Prisma. Build your app in a day and deploy it with a single CLI command."

   

The special syntax of Wasp reminds me of ballerina programming language. See cover letter gpt for code examples.

[^1]: I'll never say "transpile"

Computers

• Macbook M2 Pro 14-inch, 2023 with 16GB RAM.
• Custom built PC for Linux and Windows.
  • NixOS 24.05
  • Windows 11 dual boot

Software

• Editors: zed, sublime, and IntelliJ Idea
• Terminal: iTerm2
• Browser: Safari (default), and Edge (Work)
• RSS: reeder

Gear

• Kindle
• iPhone 11

How free software hijacked Philip Hazel's life [LWN.net]

Philip Hazel was 51 when he began the Exim message transfer agent (MTA) project in 1995, which led to the Perl-Compatible Regular Expressions (PCRE) project in 1998. At 80, he's maintained PCRE, and its successor PCRE2, for more than 27 years.

"Discipline is doing what you hate to do, but do it like you love it." -- Mike Tyson

"People of very great ability will as a rule get on better with people of very limited ability than they will with people do ordinary ability, for the same reason as the despot and the plebeian, the grandparents and the grandchildren are natural" -- Schopenhauer invented the midwit meme 200 years ago from "Essays and aphorisms".

"Anxiety is what happens when your brains are bigger than your balls. You're smart enough to know what you should be doing but lack the courage to do it. This imbalance is what triggers anxiety. The only way to demolish anxiety is to choke it out with ruthless action. This is why you never feel anxious when you're in motion, even if that motion leads to temporary failure. Anxiety has nothing to do with failure and everything to do with a lack of courage." -- x/waronweakness

Data applications (usually), web application frameworks that make it easy to publish data as dynamic reports that have an element of interactivity to them that is not possible in static reports, they are often purpose-built to tell a story or present findings backed by data.

Frameworks

evidence is a lightweight framework for building data apps using SQL. It's open source and free to get started.

observable is another example -- that uses javascript

Briefer | The collaborative data platform -- "jupyter notebooks meet Notion-like documents. Briefer is the multiplayer notebook that let's you run SQL and Python, and turn notebooks into dashboards and Data Apps.

Mercury – Build Data Web Apps in Jupyter Notebook You don't need to know frontend frameworks, HTML, CSS or JavaScript. All in pure Python without leaving Jupyter Notebook.

my mercury account

davecheney/httpstat: It's like curl -v, with colours. "It is a single file🌟 Python script that has no dependency👏 and is compatible with Python 3🍻"

--

Hurl - Run and Test HTTP Requests

Hurl is a command line tool that runs HTTP requests defined in a simple plain text format.

It can chain requests, capture values and evaluate queries on headers and body response. Hurl is very versatile: it can be used for both fetching data and testing HTTP sessions.

Hurl makes it easy to work with HTML content, REST / SOAP / GraphQL APIs, or any other XML / JSON based APIs.

• Dokku -- "The smallest PaaS implementation you've ever seen"
• piku -- "The tiniest PaaS you've ever seen. Piku allows you to do git push deployments to your own servers."
• coolify.io -- "Self-hosting with superpowers." Coolify uses nixpacks as build pack by default. nixpacks detect what kind of application are you trying to deploy and builds it accordingly.
• KubeSail -- "Run a server in your home or office that runs websites & apps, saves money, and respects your privacy." They also offer pibox a custom low-cost cluster, pre-installed with Kubernetes and the KubeSail agent. The design is based on the Raspberry Pi 4 Compute Module, includes 2 expandable SATA SSD ports, and costs $299 (June 2024). PiBox is ideal for home and small office use, and makes it easy to take advantage of KubeSail templates and backups.

--

FlightControl -  "is a PaaS that deploys to your AWS." is a "self service" alternative for render, railway, flyio, and vercel.

Here are 10 thoughts from Charlie Munger

1. Why ignoring experts is smart: "You must have the confidence to override people with more credentials whose cognition is impaired by incentive-caused bias.”

2. Intensity wins: "Passion is more important than brainpower."

3. The Roman System: "An example of a really responsible system is the system the Romans used when they built an arch. The guy who created the arch stood under it as the scaffolding was removed. It’s like packing your own parachute."

4. Just because you’ve had one misfortune doesn’t mean you should let it compound into two: "You should never, when faced with one unbelievable tragedy, let one tragedy increase into two or three because of a failure of will."

5. A forest that does not clear its deadwood with small fires will, one day, suffer a giant uncontrollable fire. Brains must clear their deadwood too. Munger: "Rapid destruction of your ideas when the time is right is one of the most valuable qualities you can acquire."

6. Your gadgets are more deadweight than they are your engines: "Look at this generation, with all of its electronic devices and multitasking. I will confidently predict less success than Warren, who just focused on reading. If you want wisdom, you’ll get it sitting on your ass. That’s the way it comes."

7. Pure thinking (not interrupted by meetings and other "tasks") is a productivity hack the world is sleeping on: "We insist on a lot of time being available almost every day to just sit and think. That is very uncommon in American business. We read and think."

8. There's a strange taboo against reading. Elon Musk has said in the new Walter Isaacson book that his parents were always trying to get him to read less. Charlie Munger said his kids laugh at his reading habit, calling him a book with two legs sticking out.

9. This mockery is misplaced. Munger: "In my whole life, I have known no wise people who didn't read all the time - none, zero." Without books, travel, and aggressive independent thinking, there is no way for you to leave the intellectual context you were born in.

10. Only high-trust tribes build civilization: "The highest form that civilization can reach is a seamless web of deserved trust—not much procedure, just totally reliable people correctly trusting one another."

Mungerisms

via X/aschwags3

1. Write your obituary and live it backwards.
2. The really big opportunities in life will be very few. So when you find a lollapalooza, and you can see it, don't hang back like a timid rabbit. Step boldly and grab it. And don't do it small.
3. Learn the big ideas in all the disciplines. Pay no heed to sectoral boundaries. And cross-apply like crazy.
4. Whenever you think something or some person is ruining your life, it's you. A victimization mentality is so debilitating
5. A lot of success in life and business comes from knowing what you want to avoid: early death, a bad marriage
6. Go to sleep each night a little less stupid than you were when you woke up.
7. Never, ever, think about something else when you should be thinking about the power of incentives
8. Assume life will be really tough, and then ask if you can handle it. If the answer is yes, you've won.
9. Do what you like and are good at. Three rules for a career: Don't sell anything you wouldn't buy yourself; Don't work for anyone you don't respect and admire; Work only with people you enjoy
10. It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid.

Course notes from Building Multimodal Search and RAG about Multimodal Learning.

• Instructor: Sebastian Witalec, head of developer relations at Weaviate,
• human's learn multi-modally
• human's foundational knowledge is built using multi-modal interaction with the world and not via language.
• multi-modal embedding models produce a joint embedding space that understand all your modalities (e.g.: text, video, audio, picture).
• Training:
  • start with specialist models
  • unify these models
  • the vectors that they generate are going to be similar
  • Models are unified using a process called contrastive representative learning.
    • CRL is a general purpose process that can be used to train any embedding model.
    • create one unified vector space representation for multiple modalities
      • by giving positive and negative examples, we train the models to pull closer vectors together for similar examples. and push away dissimilar examples
      • Anchor point
      • The pushing pulling process is achieved with the contrastive loss function.
        • encode the anchor and the (+ve and -ve ) examples into vector embeddings.
        • calculate the distance between the anchor and the examples.
        • minimize the distance between the positive example and maximize the negative example during the training process.
        • in multimodal learning, the examples can be from different modalities.
        • Minimize the loss... (Girdhar et al. 2023)

   

[via](https://learn.deeplearning.ai/courses/building-multimodal-search-and-rag/lesson/2/overview-of-multimodality)

References

• Girdhar, El-Nouby, Liu, Singh, Alwala, Joulin, Misra (2023). Imagebind: One Embedding Space to Bind Them All.