The Massively Multilingual Speech (MMS) project expands speech technology from about 100 languages to over 1,000 by building a single multilingual speech recognition model supporting over 1,100 languages (more than 10 times as many as before), language identification models able to identify over 4,000 languages (40 times more than before), pretrained models supporting over 1,400 languages, and text-to-speech models for over 1,100 languages. Our goal is to make it easier for people to access information and to use devices in their preferred language.
PaLM 2 is our next generation large language model that builds on Google’s legacy of breakthrough research in machine learning and responsible AI.
It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency, and natural language generation better than our previous state-of-the-art LLMs, including PaLM. It can accomplish these tasks because of the way it was built – bringing together compute-optimal scaling, an improved dataset mixture, and model architecture improvements.
PaLM 2 is grounded in Google’s approach to building and deploying AI responsibly. It was evaluated rigorously for its potential harms and biases, capabilities and downstream uses in research and in-product applications. It’s being used in other state-of-the-art models, like Med-PaLM 2 and Sec-PaLM, and is powering generative AI features and tools at Google, like Bard and the PaLM API.
Transformers Agent...provides a natural language API on top of transformers: we define a set of curated tools and design an agent to interpret natural language and to use these tools. It is extensible by design; we curated some relevant tools, but we’ll show you how the system can be extended easily to use any tool developed by the community.
Whether you’re learning a new library or API or you’ve been using it for years, it can feel like the documentation gets in your way more than it helps. Maybe the tutorials are too basic, or the reference manual is too sketchy, or the relevant information is split across multiple pages full of irrelevant details.
We’re exploring a way to get you the information you need, faster. By surfacing the most relevant content for questions with tailored summaries that help connect the dots, Copilot for docs saves developers from scouring reams of documentation.
In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications. Using the OpenAI API, you’ll be able to quickly build capabilities that learn to innovate and create value in ways that were cost-prohibitive, highly technical, or simply impossible before now.
...ImageBind, the first AI model capable of binding information from six modalities. The model learns a single embedding, or shared representation space, not just for text, image/video, and audio, but also for sensors that record depth (3D), thermal (infrared radiation), and inertial measurement units (IMU), which calculate motion and position.
This paper applies automation to the problem of scaling an interpretability technique to all the neurons in a large language model. Our hope is that building on this approach of automating interpretability will enable us to comprehensively audit the safety of models before deployment.
Our technique seeks to explain what patterns in text cause a neuron to activate. It consists of three steps:
- Explain the neuron's activations using GPT-4
- Simulate activations using GPT-4, conditioning on the explanation
- Score the explanation by comparing the simulated and real activations
...as models get larger and larger, full fine-tuning becomes infeasible to train on consumer hardware. In addition, storing and deploying fine-tuned models independently for each downstream task becomes very expensive, because fine-tuned models are the same size as the original pretrained model. Parameter-Efficient Fine-tuning (PEFT) approaches are meant to address both problems!
PEFT approaches only fine-tune a small number of (extra) model parameters while freezing most parameters of the pretrained LLMs, thereby greatly decreasing the computational and storage costs. This also overcomes the issues of catastrophic forgetting, a behaviour observed during the full finetuning of LLMs. PEFT approaches have also shown to be better than fine-tuning in the low-data regimes and generalize better to out-of-domain scenarios. It can be applied to various modalities, e.g., image classification and stable diffusion dreambooth.
you can think of online/offline as part of the same continuum just different measurements of latency. There are gradations of latency when you’re “online”, and “offline” is merely at the slowest end of that spectrum.
LLaVA represents a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding, achieving impressive chat capabilities mimicking spirits of the multimodal GPT-4 and setting a new state-of-the-art accuracy on Science QA.
Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks in the language domain, but the idea is less explored in the multimodal field.
1. Multimodal Instruct Data. We present the first attempt to use language-only GPT-4 to generate multimodal language-image instruction-following data. 2. LLaVA Model. We introduce LLaVA (Large Language-and-Vision Assistant), an end-to-end trained large multimodal model that connects a vision encoder and LLM for general-purpose visual and language understanding. 3. Performance. Our early experiments show that LLaVA demonstrates impressive multimodel chat abilities, sometimes exhibiting the behaviors of multimodal GPT-4 on unseen images/instructions, and yields a 85.1% relative score compared with GPT-4 on a synthetic multimodal instruction-following dataset. When fine-tuned on Science QA, the synergy of LLaVA and GPT-4 achieves a new state-of-the-art accuracy of 92.53%. 4. Open-source. We make GPT-4 generated visual instruction tuning data, our model and code base publicly available.
The WebGPU API enables web developers to use the underlying system's GPU (Graphics Processing Unit) to carry out high-performance computations and draw complex images that can be rendered in the browser.
Diffusion models have made significant breakthroughs in image, audio, and video generation, but they depend on an iterative generation process that causes slow sampling speed and caps their potential for real-time applications. To overcome this limitation, we propose consistency models, a new family of generative models that achieve high sample quality without adversarial training. They support fast one-step generation by design, while still allowing for few-step sampling to trade compute for sample quality. They also support zero-shot data editing, like image inpainting, colorization, and super-resolution, without requiring explicit training on these tasks. Consistency models can be trained either as a way to distill pre-trained diffusion models, or as standalone generative models. Through extensive experiments, we demonstrate that they outperform existing distillation techniques for diffusion models in one- and few-step generation. For example, we achieve the new state-of-the-art FID of 3.55 on CIFAR-10 and 6.20 on ImageNet 64x64 for one-step generation. When trained as standalone generative models, consistency models also outperform single-step, non-adversarial generative models on standard benchmarks like CIFAR-10, ImageNet 64x64 and LSUN 256x256.
In this paper, we introduce generative agents—computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate conversations; they remember and reflect on days past as they plan the next day. To enable generative agents, we describe an architecture that extends a large language model to store a complete record of the agent’s experiences using natural language, synthesize those memories over time into higher-level reflections, and retrieve them dynamically to plan behavior. We instantiate generative agents to populate an interactive sandbox environment inspired by The Sims, where end users can interact with a small town of twenty five agents using natural language. In an evaluation, these generative agents produce believable individual and emergent social behaviors...
By fusing large language models with computational, interactive agents, this work introduces architectural and interaction patterns for enabling believable simulations of human behavior.
...Koala, a chatbot trained by fine-tuning Meta’s LLaMA on dialogue data gathered from the web.
Many of the most capable LLMs require huge computational resources to train, and oftentimes use large and proprietary datasets. This suggests that in the future, highly capable LLMs will be largely controlled by a small number of organizations, and both users and researchers will pay to interact with these models without direct access to modify and improve them on their own. On the other hand, recent months have also seen the release of increasingly capable freely available or (partially) open-source models, such as LLaMA. These systems typically fall short of the most capable closed models, but their capabilities have been rapidly improving. This presents the community with an important question: will the future see increasingly more consolidation around a handful of closed-source models, or the growth of open models with smaller architectures that approach the performance of their larger but closed-source cousins?
Our results suggest that learning from high-quality datasets can mitigate some of the shortcomings of smaller models, maybe even matching the capabilities of large closed-source models in the future.
From Deep Learning Foundations to Stable Diffusion...is part 2 of Practical Deep Learning for Coders.
In this course, containing over 30 hours of video content, we implement the astounding Stable Diffusion algorithm from scratch!
The "Schillace Laws" were formulated after working with a variety of Large Language Model (LLM) AI systems to date. Knowing them will accelerate your journey into this exciting space of reimagining the future of software engineering.
On February 1, we stopped working on what we're now calling "darklang-classic", and are fully heads down on building "darklang-gpt", which is the same core Darklang but redesigned to have AI as the primary (or possibly only) way of writing code.
...OpenFlamingo, an open-source reproduction of DeepMind's Flamingo model. At its core, OpenFlamingo is a framework that enables training and evaluation of large multimodal models (LMMs).
Cerebras open sources seven GPT-3 models from 111 million to 13 billion parameters. Trained using the Chinchilla formula, these models set new benchmarks for accuracy and compute efficiency.
Today’s release is designed to be used by and reproducible by anyone. All models, weights, and checkpoints are available on Hugging Face and GitHub under the Apache 2.0 license. Additionally, we provide detailed information on our training methods and performance results in our forthcoming paper. The Cerebras CS-2 systems used for training are also available on-demand via Cerebras Model Studio.
This post only focuses on prompt engineering for autoregressive language models, so nothing with Cloze tests, image generation or multimodality models. At its core, the goal of prompt engineering is about alignment and model steerability.
GPT-4 can accept images as inputs and generate captions, classifications, and analyses.
GPT-4 is capable of handling over 25,000 words of text, allowing for use cases like long form content creation, extended conversations, and document search and analysis.
We are releasing our findings about an instruction-following language model, dubbed Alpaca, which is fine-tuned from Meta’s LLaMA 7B model. We train the Alpaca model on 52K instruction-following demonstrations generated in the style of self-instruct using text-davinci-003. Alpaca shows many behaviors similar to OpenAI’s text-davinci-003, but is also surprisingly small and easy/cheap to reproduce.
AI-based applications will be completely different than those we have today. The new architecture will be a far more elegant, four-component structure based around GPTs: State, Policy, Questions, and Action.
A security program using SPQA
Choose the base model — You start with the latest and greatest overall GPT model from OpenAI, Google, Meta, McKinsey, or whoever. Lots of companies will have one. Let’s call it OpenAI’s GPT-6. It already knows so incredibly much about security, biotech, project management, scheduling, meetings, budgets, incident response, and audit preparedness that you might be able to survive with it alone. But you need more personalized context.
Train your custom model — Then you train your custom model which is based on your own data, which will stack on top of GPT-6. This is all the stuff in the STATE section above. It’s your company’s telemetry and context. Logs. Docs. Finances. Chats. Emails. Meeting transcripts. Everything. It’s a small company and there are compression algorithms as part of the Custom Model Generation (CMG) product we use, so it’s a total of 312TB of data. You train your custom model on that.
Train your policy model — Now you train another model that’s all about your company’s desires. The mission, the goals, your anti-goals, your challenges, your strategies. This is the guidance that comes from humans that we’re using to steer the ACTION part of the architecture. When we ask it to make stuff for us, and build out our plans, it’ll do so using the guardrails captured here in the POLICY.
Tell the system to take the following actions — Now the models are combined. We have GPT-6, stacked with our STATE model, also stacked with our POLICY model, and together they know us better than we know ourselves.
The race is on to release the first fully open language model that gives people ChatGPT-like capabilities on their own devices.
Bitwarden expands the Log in with device option that lets you use a second device to authenticate your Bitwarden vault login instead of using your Bitwarden password.
Data-Centric AI (DCAI) is an emerging science that studies techniques to improve datasets, which is often the best way to improve performance in practical ML applications. While good data scientists have long practiced this manually via ad hoc trial/error and intuition, DCAI considers the improvement of data as a systematic engineering discipline.
This is the first-ever course on DCAI. This class covers algorithms to find and fix common issues in ML data and to construct better datasets, concentrating on data used in supervised learning tasks like classification. All material taught in this course is highly practical, focused on impactful aspects of real-world ML applications, rather than mathematical details of how particular models work. You can take this course to learn practical techniques not covered in most ML classes, which will help mitigate the “garbage in, garbage out” problem that plagues many real-world ML applications.
The “classical stack” of Software 1.0 is what we’re all familiar with — it is written in languages such as Python, C++, etc...Software 2.0 is written in much more abstract, human unfriendly language, such as the weights of a neural network.
Benefits of Software 2.0
- Computationally homogeneous
- Simple to bake into silicon
- Constant running time
- Constant memory use
- Highly portable
- Modules can meld into an optimal whole
- It is better than you
Limitations of Software 2.0
At the end of the optimization we’re left with large networks that work well, but it’s very hard to tell how. Across many applications areas, we’ll be left with a choice of using a 90% accurate model we understand, or 99% accurate model we don’t.
The 2.0 stack can fail in unintuitive and embarrassing ways ,or worse, they can “silently fail”
...the existence of adversarial examples and attacks highlights the unintuitive nature of this stack.
Programming Software 2.0
If you recognize Software 2.0 as a new and emerging programming paradigm instead of simply treating neural networks as a pretty good classifier in the class of machine learning techniques, the extrapolations become more obvious, and it’s clear that there is much more work to do.
In particular, we’ve built up a vast amount of tooling that assists humans in writing 1.0 code, such as powerful IDEs with features like syntax highlighting, debuggers, profilers, go to def, git integration, etc. In the 2.0 stack, the programming is done by accumulating, massaging and cleaning datasets. Who is going to develop the first Software 2.0 IDEs, which help with all of the workflows in accumulating, visualizing, cleaning, labeling, and sourcing datasets?
Github is a very successful home for Software 1.0 code. Is there space for a Software 2.0 Github? In this case repositories are datasets and commits are made up of additions and edits of the labels.
Traditional package managers and related serving infrastructure like pip, conda, docker, etc. help us more easily deploy and compose binaries. How do we effectively deploy, share, import and work with Software 2.0 binaries? What is the conda equivalent for neural networks?
This guide introduces BLIP-2 from Salesforce Research that enables a suite of state-of-the-art visual-language models that are now available in 🤗 Transformers. We'll show you how to use it for image captioning, prompted image captioning, visual question-answering, and chat-based prompting.
BLIP-2 bridges the modality gap between vision and language models by adding a lightweight Querying Transformer (Q-Former) between an off-the-shelf frozen pre-trained image encoder and a frozen large language model. Q-Former is the only trainable part of BLIP-2; both the image encoder and language model remain frozen.
At their core, modern ML systems have complex mathematical models that use training data to become competent at a task. And while there are new risks inherent in the ML model, all of that complexity still runs in software. Training data are still stored in memory somewhere. And all of that is on a computer, on a network, and attached to the Internet. Like everything else, these systems will be hacked through vulnerabilities in those more conventional parts of the system.
LMOps is a research initiative on fundamental research and technology for building AI products w/ foundation models, especially on the general technology for enabling AI capabilities w/ LLMs and Generative AI models.
- Better Prompts: Promptist, Extensible prompts
- Longer Context: Structured prompting, Length-Extrapolatable Transformers
- Knowledge Augmentation (TBA)
A few updates I found interesting.
The Beauty of languages: You can now use your own voice during a translated call in Skype.
Universal translator: During a Skype call, if a participant speaks different languages, Skype Translator will automatically detect the languages and translate it for you.
Extra! Extra! Read all about it: Stay up-to-date with the latest news and trends.
Hit me up sometime: You can easily add contacts in Skype on mobile using a unique QR code to get connected.
I have a few thoughts on the Today feature and overall updates Skype has been receiving over the past few months but I'll leave those for another post.
Testing WebmentionFs send integration. From Website.
As someone who spends a significant amount of time in the browser, making Edge, more specifically the browser the platform for applications, this looks appealing. Especially when you consider Progressive Web App (PWA) support and integrations with the Windows Store.
Automattic, the current owner of tumblr, one of the biggest meme mines in the world, has said they’re going to implement ActivityPub, which is the underlying protocol on which Mastodon operates. There are boring ways this could go, and then interesting ways this could go.
Interesting points. I'm looking forward to how this shakes out.
Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
if own your domain, create value there, and drive people to it, you’re paying ~$10 a year to build unbounded value over the years — value you control.
That is why owning a domain (and publishing your content there) is like planting a tree: it’s value that starts small and grows. The best time to own a domain and publish your content there was 20 years ago. The second best time is today.
I love a technology like
rel=mewhich pushes the idea of domain ownership into broader and broader spheres of society — “How do I get that nice little green checkmark on my profile?” It reinforces the value of owning your own domain (which you can verify elsewhere) and encourages citizens of the internet people to build value in their own little corners of the world wide web.
This article answers three common questions about how being open source strengthens Bitwarden security, transparency, and privacy.
Here's how to do this:
- Run a text search (or a semantic search, described later) against your documentation to find content that looks like it could be relevant to the user's question.
- Grab extracts of that content and glue them all together into a blob of text.
- Construct a prompt consisting of that text followed by "Given the above content, answer the following question: " and the user's question
- Send the whole thing through the GPT-3 API and see what comes back
Wouldn’t it be amazing if a similar phrase could enter the larger public consciousness for blogs or even people who you follow online?
“Follow me on Twitter.” “I’m @realChuckieCheese on Instagram.” “Subscribe to my videos on YouTube.”
You’d hear some popular influencer saying:
“Follow me wherever you follow people online.” “Find me and subscribe wherever you get your content.”
In a world like this, perhaps apex domains could become the currency of online handles: follow me
Now the only challenges for me are:
- Should the song on my website match my ringtone?
- Where do I place the flames GIF?
If you're looking for new folks follow, here's a list of blogs on a variety of topics.
The article suggests these processors are for the education market. Hopefully a few of the devices with these processors in a Surface Go form-factor are made generally available as well. I think the N200 series is the sweet spot in terms of performance and battery life with only 6W of max turbo power. The i3 which draws a max of 15W may be too much. At that point, some of the newly announced U-series processors might make more sense.
For me, I've found POSSE to Twitter and Mastodon using RSS and IFTTT-like services has been a relatively low-effort thing to do. The downside though is any follow-up conversations take place on those platforms. That hasn't been an issue for me yet though so until it is, I'll continue to use my relatively low-effort solution.
I agree with you on likes / reposts. My current implementation of those posts is focused on Webmentions, which means it's virtually meaningless since few people know about let alone integrate Webmentions into their website. I would argue replies tend to fall into that same space as well. I have however found great use in bookmark posts to which I try and add some content from the source document to help me quickly identfy why I thought that post / website was interesting or relevant to a specific topic at that time.
The simplest, fastest repository for training/finetuning medium-sized GPTs. It's a re-write of minGPT, which I think became too complicated, and which I am hesitant to now touch. Still under active development, currently working to reproduce GPT-2 on OpenWebText dataset. The code itself aims by design to be plain and readable: train.py is a ~300-line boilerplate training loop and model.py a ~300-line GPT model definition, which can optionally load the GPT-2 weights from OpenAI. That's it.
Run 100B+ language models at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
In the beginning, there were blogs, and they were the original social web. We built community. We found our people. We wrote personally. We wrote frequently. We self-policed, and we linked to each other so that newbies could discover new and good blogs.
The biggest reason personal blogs need to make a comeback is a simple one: we should all be in control of our own platforms.
People built entire communities around their favorite blogs, and it was a good thing. You could find your people, build your tribe, and discuss the things your collective found important.
Buy that domain name. Carve your space out on the web. Tell your stories, build your community, and talk to your people. It doesn’t have to be big. It doesn’t have to be fancy. You don’t have to reinvent the wheel. It doesn’t need to duplicate any space that already exists on the web — in fact, it shouldn’t. This is your creation. It’s your expression. It should reflect you.
The new model,
text-embedding-ada-002, replaces five separate models for text search, text similarity, and code search, and outperforms our previous most capable model, Davinci, at most tasks, while being priced 99.8% lower.
We all mourned when Reader died and took RSS with it, but it's time to return to what made it great
Really cool project. Don't really care for the crypto stuff but the rest looks very interesting.
These updates are exciting!
Reddit appears to be building out new Chat functionality using Matrix
Discourse is working on adding Matrix support
Thunderbird launched Matrix support.
Automattic is busy building Matrix plugins for Wordpress
Not as exciting
...only a handful of these initiatives have resulted in funding reaching the core Matrix team. This is directly putting core Matrix development at risk.
In short: folks love the amazing decentralised encrypted comms utopia of Matrix. But organisations also love that they can use it without having to pay anyone to develop or maintain it. This is completely unsustainable, and Element is now literally unable to fund the entirety of the Matrix Foundation on behalf of everyone else - and has had to lay off some of the folks working on the core team as a result.
In the interim, if you are an organisation who’s building on Matrix and you want the project to continue to flourish, please mail firstname.lastname@example.org to discuss how you can support the foundations that you are depending on.
I'm looking forward to the future of the Matrix protocol, especially the P2P components.
This is a four day Rust course developed by the Android team. The course covers the full spectrum of Rust, from basic syntax to advanced topics like generics and error handling. It also includes Android-specific content on the last day.
Large language models have recently shown an ability to solve a variety of problems. In this notebook we consider programming problems (as solved by AlphaCode) and mathematics problems (as solved by Minerva). The questions we would like to get at are:
- In the future, what role will these generative models play in assisting a programmer or mathematician?
- What will be a workflow that incorporates these models?
- How will other existing tools (such as programming languages) change to accomodate this workflow?
Worked well for me. Thanks for sharing!
Today we're joined by ChatGPT, the latest and coolest large language model developed by OpenAl. In our conversation with ChatGPT, we discuss the background and capabilities of large language models, the potential applications of these models, and some of the technical challenges and open questions in the field. We also explore the role of supervised learning in creating ChatGPT, and the use of PPO in training the model. Finally, we discuss the risks of misuse of large language models, and the best resources for learning more about these models and their applications.
Render markdown on the CLI
GitHub Copilot for Business gives organizations:
- The power of AI. Millions of developers have already used GitHub Copilot to build software faster, stay in the flow longer, and solve problems in new ways—all right from their editor of choice.
- Simple license management. Administrators can enable GitHub Copilot for their teams and select which organizations, teams, and developers receive licenses.
- Organization-wide policy management. You can easily set policy controls to enforce user settings for public code matching on behalf of your organization.
- Your code is safe with us. With Copilot for Business, we won’t retain code snippets, store or share your code regardless if the data is from public repositories, private repositories, non-GitHub repositories, or local files.
A container-based approach to boot a full Android system on a regular GNU/Linux system like Ubuntu.
Florence, a low-code geospatial library for everyone that ranks city places with (life-inspired) functions.
Florence heavily laverages .NET Interactive/Polyglot Notebooks runtime to hide and execute code behind the scene (including breaking some language constraints).
Microsoft Research recently open-sourced FarmVibes.AI, a suite of ML models and tools for sustainable agriculture. FarmVibes.AI includes data processing workflows for fusing multiple sets of spatiotemporal and geospatial data, such as weather data and satellite and drone imagery.
Slightly modified the original script to use Streamlink and lower quality to 240p for bandwith and resource purposes.
(require 'elfeed) (defun elfeed-v-mpv (url) "Watch a video from URL in MPV" (async-shell-command (format "streamlink -p mpv %s 240p" url))) (defun elfeed-view-mpv (&optional use-generic-p) "Youtube-feed link" (interactive "P") (let ((entries (elfeed-search-selected))) (cl-loop for entry in entries do (elfeed-untag entry 'unread) when (elfeed-entry-link entry) do (elfeed-v-mpv it)) (mapc #'elfeed-search-update-entry entries) (unless (use-region-p) (forward-line)))) (define-key elfeed-search-mode-map (kbd "v") 'elfeed-view-mpv)
We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.
PhilTel is a telephone collective based in Philadelphia, Pennsylvania, focusing on making communications accessible to everyone by installing free-to-use payphones. While you'll be able to make standard telephone calls through our phones, we're also focusing on offering interesting services or experiences. We don't want to only facilitate human-to-human interaction but also human-to-machine interaction and give people an environment where they can explore the telephone network and learn from it.
Consider timezones: engineers in Madrid and engineers in San Francisco had almost no overlap in their working hours. Good asynchronous communication was essential.
Over time, I noticed that the teams that were most effective at this scale were the teams that had a strong culture of documentation and automated testing.
As I started to work on my own array of smaller personal projects, I found that the same discipline that worked for large teams somehow sped me up, when intuitively I would have expected it to slow me down.
The Stable Diffusion 2.0 release includes robust text-to-image models trained using a brand new text encoder (OpenCLIP), developed by LAION with support from Stability AI, which greatly improves the quality of the generated images compared to earlier V1 releases.
Stable Diffusion 2.0 also includes an Upscaler Diffusion model that enhances the resolution of images by a factor of 4.
the intangible, overarching benefit of practicing meeting mindfulness is this: you spend less of your day sort-of-listening and more of your day really thinking.
Just a friendly reminder, there are alternatives.
Automattic CEO Matt Mullenweg — whose company acquired Tumblr from Verizon in 2019 — suggested...Tumblr... would soon add ...activitypub.
I'm perfectly happy using my site as the main place to post content but considering it's under new management and adopting open standards, it might be time to checkout out Tumblr again.
In the six weeks since announcing that Internet Archive has begun gathering content for the Digital Library of Amateur Radio and Communications (DLARC), the project has quickly grown to more than 25,000 items, including ham radio newsletters, podcasts, videos, books, and catalogs.
...blog posts are always async, but they can lead to conversations and debates, once the reader is done reading. There's also the nature of blog posts being one-to-many, whereas chat is many-to-many, if done in a public channel. One-to-many forms of communication should generally be more formal, but can spread ideas and thoughts more coherently than many-to-many.
Our paper books have lasted hundreds of years on our shelves and are still readable. Without active maintenance, we will be lucky if our digital books last a decade.
Feta is a Matrix server distribution for the Raspberry Pi 3 and 4.
This looks like a great project to get started with self-hosting and join the Matrix network. Having something similar for the fediverse would be great as well. I've hosted Matrix and Mastodon servers on a Raspberry Pi before so I know it's up to the task.
Here’s how it works in practice:
- A news organization (or any organization, let’s just start with news) already asserts ownership of its domain e.g. via its certificate, so we piggyback trust off its domain.
- It stands up a Mastodon or other social server at a standard address. I’d propose follow.washingtonpost.com but there’s a bunch of reasons why you might do something else, see below, and uses the agreed well-known autodiscovery protocol to return the address for its Mastodon server (but I don’t see an entry for activitypub or Mastodon yet).
- It creates accounts for its staff on its Mastodon server. Nobody else gets an account; the public can’t sign up.
What you get:
- Verified accounts. Instead of relying on a third party to “verify” your account by sticking a blue check against your display name, account provenance and “verification” is inherited as a property of the Mastodon server....
- Ease of discovery...all a user would have to do, to find Washington Post accounts to follow, would be to know the washingtonpost.com domain. Autodiscovery would let your Mastodon client point itself to the appropriate server.
Not just news organizations...anyone can set up a Mastodon server...the federation means that “official” accounts become “more official” when their server home is hung off the domain of the actual organization.
You wouldn’t need Twitter (or anyone else, really) to verify that the UK Prime Minister’s account is official, because you’d have following.gov.uk as the Mastodon server, which means you can trust that server as much as you trust .gov.uk domains.
Your university or college wants you to have a social media account? Sure, you can have it hosted at following.ucla.edu.
And yes, brands can get in on it. Sure. That way there’s a tiny chance you’re following the Proper Brand Account rather than a Parody Brand Account, which… is probably for the best. Or it’s easier to see that a Parody Account is a Parody Account because you can look at the parent server.
Communicating effectively as an engineer means empathically increasing the resolution of your writing.
...“low-resolution writing”...There is very little context, too much reliance on pronouns and unclear references. The writing is not emphatic —the reader has to spend extra energy to work out what is being said
Longer-form writing gives you an opportunity to dive deeper into why you are saying what you are saying. It is a chance to educate, to teach, to help understand and to level up.
The quality of the API documentation will carry an astronomical amount of leverage. This leverage will work in both directions. Genuinely helpful documentation is the difference between being swamped by support requests from frustrated API users and significantly increasing the usage of your service. Happy users beget more happy users.
Spoken words get forgotten. Written words are shared, preserved, and become the basis of a company's culture. source
High resolution, empathic writing...You will have to spend more energy to make your writing easy to follow. You will have to grapple with your own confusion and holes in your understanding. You will have to figure out what the appropriate density for your writing is.
It's not about you, though.. It's about them.
Not only does a single recipient benefit from your extra effort, what if ten people read your good work? A hundred? A thousand? What if the company CEO reads it? Taking writing seriously at work or in your organisation and putting in the effort to delight the reader will, over time, compound into a massive body of quality writing that benefits everyone. It is a literal win-win-win
Produce writing you would read with delight if you were on the other end.
It's also built with .NET 🙂
write your most important thoughts on your own site. You can share the link on as many platforms as you like and have conversations with anyone who wants to connect with you and your work. But nobody can take it from you. You are in control. Forever.
PyTorch is moving to the Linux Foundation (LF) as a top-level project under the name PyTorch Foundation.
The PyTorch Technical Governance now supports a hierarchical maintainer structure and clear outlining of processes around day to day work and escalations. This doesn’t change how we run things, but it does add discipline and openness that at our scale feels essential and timely.
We’ve been eager to take this step since we joined Automattic last year...
Wow. Yet another company I didn't know was owned by Automaticc (parent company of WordPress). So not only do they have a stake in regular blogs and websites, but they also are in the microblogging space with Tumblr. With Pocket Casts they're now into podcasts too. Good for them.
We believe that podcasting can not and should not be controlled by Apple and Spotify, and instead support a diverse ecosystem of third-party clients.
I couldn't agree more. Though to be fair to Apple, in all the years since podcasts have been a thing, despite them being one of the main indices, they didn't make any overt attempts to lock down the ecosystem. It's not until companies like Amazon and Spotify tried to make certain content platform exclusives that the ecosystem has started to feel more closed.
In total, we’re releasing four videos, with around 5.5 hours of content, covering the following topics (the lesson numbers start at “9”, since this is a continuation of Practical Deep Learning for Coders part 1, which had 8 lessons):
- Lesson 9 by Jeremy Howard: How to use Diffusers pipelines; What are the conceptual parts of Stable Diffusion
- Lesson 9A by Jonathan Whitaker: A deep dive into Stable Diffusion concepts and code
- Lesson 9B by Wasim Lorgat and Tanishq Abraham: The math of diffusion
- Lesson 10 by Jeremy Howard: Creating a custom diffusion pipeline; Starting “from the foundations”
My experience working on SSB (i.e. non-crypto fully decentralized protocol) is suitable for small world communication, and definitely not suitable for big world. Email proves that federation can do big world.
The conversational feed design of email inboxes, group chats, and InstaTwitBook is fleeting – they're only concerned with self-assertive immediate thoughts that rush by us in a few moments...But streams only surface the Zeitgeisty ideas of the last 24 hours...Gardens present information in a richly linked landscape that grows slowly over time...The garden helps us move away from time-bound streams and into contextual knowledge spaces.
The Six Patterns of Gardening:
- Topography over Timelines - Gardens are organised around contextual relationships and associative links; the concepts and themes within each note determine how it's connected to others.
- Continuous Growth - Gardens are never finished, they're constantly growing, evolving, and changing.
- Imperfection & Learning in Public - Gardens are imperfect by design. They don't hide their rough edges or claim to be a permanent source of truth.
- Playful, Personal, and Experimental - Gardens are non-homogenous by nature. You can plant the same seeds as your neighbour, but you'll always end up with a different arrangement of plants.
- Intercropping & Content Diversity - Gardens are not just a collection of interlinked words...Podcasts, videos, diagrams, illustrations, interactive web animations, academic papers, tweets, rough sketches, and code snippets should all live and grow in the garden.
- Independent Ownership - Gardening is about claiming a small patch of the web for yourself, one you fully own and control... If you give it a bit of forethought, you can build your garden in a way that makes it easy to transfer and adapt. Platforms and technologies will inevitably change. Using old-school, reliable, and widely used web native formats like HTML/CSS is a safe bet.
Bluesky was created to build a social protocol. In the spring, we released “ADX,” the very first iteration of the protocol...ADX is now the “Authenticated Transport Protocol"...more simply, the “AT Protocol.”
The “AT Protocol” is a new federated social network
What makes AT Protocol unique:
- Account portability
- Algorithmic choice
Here are a bunch of not-so-obvious lessons I’ve internalized through writing each day:
- Writing can be a starting point, not an ending one
- Write to think
- The power of DIFY: Do it for yourself, don’t think too much about what you want other people to get out of it.
- Think small
- Gain energy
- A lot of books are collections of blog posts
- Small is an unblocker
This sample shows how to use a pretrained Bidirectional Attention Flow (BiDAF) ONNX model in ML.NET for answering a query about a given context paragraph.
The Web Almanac is a comprehensive report on the state of the web, backed by real data and trusted web experts. The 2022 edition is comprised of 23 chapters spanning aspects of page content, user experience, publishing, and distribution.
Readium LCP was developed five years ago to protect digital files from unauthorized distribution. Unlike proprietary platforms, the technology is open to anyone who wants to look inside the codebase and make improvements. It is a promising alternative for libraries and users wanting to avoid the limitations of traditional DRM.
This dataset contains detailed data on 42,207 apartments (242,257 rooms) in 3,093 buildings including their geometries, room typology as well as their visual, acoustical, topological and daylight characteristics.
Large language models (LLMs) have shown exceptional performance on a variety of natural language tasks. Yet, their capabilities for HTML understanding...have not been fully explored. We contribute HTML understanding models (fine-tuned LLMs) and an in-depth analysis of their capabilities under three tasks: (i) Semantic Classification of HTML elements, (ii) Description Generation for HTML inputs, and (iii) Autonomous Web Navigation of HTML pages.
Out of the LLMs we evaluate, we show evidence that T5-based models are ideal due to their bidirectional encoder-decoder architecture.
Python and SQL remain the two most common programming skills for data scientists
VSCode is now used by over 50% of working data scientists
Notebooks are a popular environment as well.
Colab notebooks are the most popular cloud-based Jupyter notebook environment
Makes sense especially since Kaggle is owned by Google.
Kaggle DS & ML Survey 2022 Scikit-learn is the most popular ML framework while PyTorch has been growing steadily year-over-year
LightGBM, XGBoost are also among the top frameworks.
Transformer architectures are becoming more popular for deep learning models (both image and text data)
All major cloud computing providers saw strong year over year growth in 2022
Specialized hardware like Tensor Processing Units (TPUs) is gaining initial traction with Kaggle data scientists
I got serious about consolidating the media my family consumes; I decided to buy blu-ray and DVD copies of all the movies and TV shows we actually cared about, and rip them onto a NAS.
I'm glad I've gone down this path, and become more intentional about my media consumption, especially as companies are deleting already-purchased content from users' media libraries! It's sickening (and, IMHO, should be illegal) they can show a 'buy' button for a DRM'ed digital downloads that the user never actually 'owns'.
Couldn't agree more. Although the focus of this post is on video, you can say the same for music and books.
I spent great time, energy and money, over many years to create the writing and programming environment I wanted to use and I wanted my peers to use, so we could work together to create species-saving communication tools, and just beauty...
...I read the story of David Bowie's last days, he did something amazing when he knew he had a short time to live. He stepped back and got out of the way. He understood this is no longer his world.
When you're young, you think expansively, and as you get old reality sinks in and your imagination contracts. The horizon gets closer and closer. We don't get to mold the world, we are not gods, no matter how good or generous, smart of ruthless you may be, we all start out young and if we're lucky we get old and then we're gone.
- New independent research labs are rapidly open sourcing the closed source output of major labs.
- Safety is gaining awareness among major AI research entities
- The China-US AI research gap has continued to widen
- AI-driven scientific research continues to lead to breakthroughs
In this course, students will learn to develop complex system-level software in the C programming language while gaining an intimate understanding of the Unix operating system (and all OS that belong to this family, such as Linux, the BSDs, and even Mac OS X) and its programming environment.
Topics covered will include the user/kernel interface, fundamental concepts of Unix, user authentication, basic and advanced I/O, fileystems, signals, process relationships, and interprocess communication. Fundamental concepts of software development and maintenance on Unix systems (development and debugging tools such as "make" and "gdb") will also be covered.
...backdoors can be added during compilation, circumventing any safeguards in the data preparation and model training stages.
some backdoors, such as ImpNet, can only be reliably detected at the stage where they are inserted and removing them anywhere else presents a significant challenge.
machine-learning model security requires assurance of provenance along the entire technical pipeline, including the data, model architecture, compiler, and hardware specification.
A bookmark (or linkblog) is a post that is primarily comprised of a URL, often title text from that URL, sometimes optional text describing, tagging, or quoting from its contents.
Bookmarks are useful for saving things to read later or build a recommended reading list.
Both this post as well as Tom MacWright's "How to Blog" resonate. I've been posting more consistently to my microblog feeds. These posts are more informal, but just the aspect of producing something even if it's just a short snippet is gratifying. The informality of it makes the posts significantly shorter but the pace at which I publish content and share ideas is faster.
It's always fun to stumble upon these lists and finding more interesting people and websites to follow.
Interesting discussion at about 21:30 on a federated wiki / review aggregator.
Google+ was Google trying to mimic the walled garden of Facebook — their “how” of extracting value from the people of the internet. But they already had an answer for Facebook’s News Feed in front of them: Blogger / Google Reader, the read / write of the internet.
They provide the tools – Reader, Blogger, Search — we provide the personal websites. The open, accessible, indexable web as The Next Great Social Network.
I've been doing something similar to readlists, except with RSS feeds. I create a custom recipe in Calibre which pulls and aggregates the 50 latest articles for each feed in my recipe. I limit it to only look at articles published in the past day since I do this every evening. Think of it like the evening paper. The result is an EPUB file which I then import into my e-book reader.
A few advantages I've found to doing this are:
- I take a break from the computer.
- Since the e-book reader is offline, I focus on reading the article and don't have the option to click on links and get distracted browsing the internet.
- Since I'm already using the e-book reader, it's easy to transition to reading a book.
Can't believe this is the first time I'd heard of this desktop app. Usually using mobile apps like Sky Guide is convenient when on the go, but Stellarium not only seems to have lots of information, but also cross-platform and web-based.
This ☝️. If you know, you know. 🔥
It feels like the 2022 conference was just yesterday. In any case, save the date February 4-5,2023.
Good read. Other than Emacs, Joplin is my go-to notetaking application.
Matrix Rain sample with different variations.
an alternative...emoji set.
W3C’s Web Accessibility Initiative provides strategies, standards, and resources to ensure that the internet is accessible for as many people as possible. The guidelines that underpin these standards are called the Web Content Accessibility Guidelines, or WCAG.
Color contrast is an important piece of the puzzle for accessibility on the web, and adhering to it makes the web more usable for the greatest number of people in the most varied situations.
Apps to test contrast:
- Chrome Dev Tools
High-perf, scalable array storage that can be used for scenarios like language models.
- Create global configuration
- Set default name
- Set default email address
- Set default branch name
- Set default editor
When you liberate programming from the requirement to be general and professional and scalable, it becomes a different activity altogether, just as cooking at home is really nothing like cooking in a commercial kitchen.
Same goes for websites and self-hosting.
I'm not an Apple user, but this is cool.
Influence & managing up: Enact positive change for yourself, your team, or the whole organization.
Leading through crises: Strengthen your support network, meet your team where they’re at, and weather the tough times.
Cross-functional relationships: Strengthen relationships by creating role clarity and creatively supporting one another.
One-on-ones: Set your teammates up for success during your one-on-one meetings!
Hiring: Build consistent, repeatable, and equitable interviews and onboarding plans.
Meetings: Support participants, hone the content, and nail the meeting goal.
Feedback & performance reviews: Everyone deserves clear, actionable feedback!
Communication & team dynamics: Plan ahead, facilitate well, and create clarity.
Adapting your approach: As your work context and team evolves, your leadership approach will need to evolve, too.
- Dot Product
...about 1% of Internet users create content, while 99% are just consumers of that content
What have I learned from YC's users, the startups we've funded?
...most startups have the same problems.
...the batch that broke YC was a powerful demonstration of how individualized the process of advising startups has to be.
...founders can be [bad] at realizing what their problems are. Founders will sometimes come in to talk about some problem, and we'll discover another much bigger one in the course of the conversation.
Often founders know what their problems are, but not their relative importance.
Focus is doubly important for early stage startups, because not only do they have a hundred different problems, they don't have anyone to work on them except the founders. If the founders focus on things that don't matter, there's no one focusing on the things that do.
Speed defines startups. Focus enables speed. YC improves focus.
Why are founders uncertain about what to do? Partly because startups almost by definition are doing something new, which means no one knows how to do it yet, or in most cases even what "it" is.
disgruntled Facebook users keep using the service because they don’t want to leave behind their friends, family, communities and customers.
“How to Ditch Facebook Without Losing Your Friends” explains the rationale behind these proposals - and offers a tour of what it would be like to use a federated, interoperable Facebook, from setting up your account to protecting your privacy and taking control of your own community’s moderation policies, overriding the limits and permissions that Facebook has unilaterally imposed on its users.
This tool will help you to create a Firefox profile with the defaults you like.
You select which features you want to enable and disable and in the end you get a download link for a zip-file with your profile template.
20 years and still going strong.
This is my comment 2
...2022 Netherlands WordCamp edition in Arnhem [presentation] on turning all WordPress sites into fully IndieWeb enabled sites. Meaning turning well over a third of the web into the open social web. Outside all the silos.
When Lisp adopts a new paradigm it not only replicates existing practice, but goes beyond it to become a testbed for advancing the state of the art. Why has Lisp been able to adapt so easily when other languages have not? One reason is that Lisp is a programmable programming language.
- Education & Teaching
- Health & Medicine
- Social Sciences
- Information Security (InfoSec)
- Computer Science
- Data Science
- Personal Development
- Art & Design
The OBI system is open source, collaborative and distributed.
Our focus is on low cost and rapidly-built structures that are modular, ecological, and energy efficient.
...internally public blogs written by members of the...squad detailing what they’re working on and thinking about.
...a guide for economists on what programming is, why it’s useful, and how to do it.
This repository contains the source for the slides and the exercises used in the Haskell trainings at Google.
Discover 350+ popular open source alternatives to your proprietary SaaS.
Open Library is an initiative of the Internet Archive, a 501(c)(3) non-profit, building a digital library of Internet sites and other cultural artifacts in digital form.
Find feeds for all of your favorite sites and keep up with everything they post!
Commonplace is an ideal medium for the curation and cultivation of intellectual ideas, thoughts, and knowledge. It’s also a proven and timeless system, tested by folks from a spectrum of backgrounds including authors, professors, and scientists.
- Remember things
- Write to recall
- Understand reading
- Personal reference system
- Filter ideas
- Unleash creativity
Reflecting on your commonplace
The most profound power of your commonplace is being able to thumb through reading and review material. Your commonplace book isn’t just a filing cabinet—it’s an evolving record of your life and observations.
...the kind of web they define themselves against; that kind of bloated, corporate, algorithm-ruled and ad-ridden mess that constitutes the majority of highly-trafficked websites these day.
...for me, the term “Small Web” refers to a couple of main things: independence from tech giants, and websites that are lightweight and high-performance.
- A late 90s-style, hand-crafted web
- Alternative protocols, like Gemini
- An independent web
Blot is a blogging platform with no interface. It turns a folder into a website.
Curated list of awesome OpenSteetMap-projects
This site is dedicated to a community (and a larger movement) about the internet how it's changed. We are creating, discovering and enjoying websites and digital spaces.
A virtual conference exploring what the internet could become over the next decade
- Pioneering Alternative Models for Community on the Internet
- Misinformation, Disinformation, and Media Literacy in a Less-Centralized Social Media Universe
- Interoperability and Alternative Social Media
- Lessons from Experiments in Local Community-Building
- Deplatforming and Innovation
- New Directions in Social Media Research
...masterWiki is the direct adaptation of MasterClass' video courses translated into wikiHow-style how-to guides...
Here’s how to read the post:
- Level 1 — Casual. Read the headlines — figure out the details yourself. Most of this isn’t rocket science.
- Level 2 — Tutorial. Read the steps underneath the headline. I’ve spelled out every step so that you can save your brain power for something else.
- Level 3 — Productivity Nerd. Below the tutorial steps, I’ve included discussion of the behavior design implications. This is for true productivity nerds, i.e. the readers of Better Humans.
Optimize First for Single Tasking
#1. Turn OFF (almost) all notifications
#2. Hide social media slot machines
#3. Hide messaging slot machines
#4. Disable app review requests
#5. Turn on Do Not Disturb
#6. Be strategic about your wallpaper
#7. Turn off Raise to Wake
#8. Add the Screen Time widget
#9. Add Content Restrictions
#10. (Optional) Use Restrictions to turn off Safari
#11. Organize your Apps and Folders alphabetically
Switch to Google Cloud to Work Faster
#12. Choose GMail
#13. Choose Google Calendar
#14. Replace Apple Maps with Google Maps
#15. Install the GBoard keyboard for faster typing
#16. Switch to Google Photos
Install These Apps for Productivity
#17. Use Evernote for all note taking, to-do lists, everything
#18. The Case for Calm as your go-to meditation app
#19. Install the right goal tracker for you
#20. Store all your passwords in a password manager, probably LastPass
#21. Use Numerical as your default calculator
#22. Put the Camera app in your toolbar
#23. Use this Doppler Radar app
#24. Use this Pomodoro app
#25. Use Brain.fm for background noise
Use These Apps and Configurations for Deep Learning
#26. Subscribe to these podcasts
#27. Install the Kindle app but never read it in bed
#28. Use Safari this way
#29. Organize your home screen for deep learning over shallow learning
Use These Apps and Configurations for Longevity
#30. Track steps this way
#31. Prefer Time Restricted Eating Over Calorie Counting
#32. Schedule Night Shift
#33. Set up Medical ID
Make The Finishing Touches with These Configurations
#34. Change Siri to a man
#35. Change your phone’s name
#36. Turn off advertising tracking
#37. Set auto-lock to the maximum time
#38. Set your personal hotspot password to a random three word phrase
#39. Turn on control center everywhere
#40. Turn on Background App Refresh
#41. Delete Garage Band
#42. Develop verbal memory for talking to Siri
#43. Set up these text replacement shortcuts
#44. Set your address
#45. Backup this way
- Discover and learn to use the basic functions of the following software:
- Learn how to use these different software programs together to manage information using the following methods:
- The Zettelkasten method
- The P.A.R.A method
- The inbox method
A free course designed for people with some coding experience, who want to learn how to apply deep learning and machine learning to practical problems.
- Getting started
- Neural net foundations
- Natural Language (NLP)
- From-scratch Model
- Random forests
- Collaborative filtering and embeddings
- Convolutions (CNNs)