The hottest Technology Substack posts right now

And their main takeaways
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Top Technology Topics

VERSES KOSM™ OS Slashes Developer Barrier to Entry for Building AI Apps

Spatial Web AI by Denise Holt • 0 implied HN points • 06 Feb 23
🕹 Technology AI Operating System Spatial Web Artificial Intelligence
  1. Building AI apps traditionally takes a lot of time and money, but VERSES Genius™ offers a way to do it easily and creatively with their innovative developer kit.
  2. Unlike traditional AI systems, VERSES creates a network of intelligence that evolves and updates in real-time, enabling contextual awareness within computing power.
  3. VERSES Genius™ platform introduces a new way of AI operation, using the Active Inference AI method, enabling intelligent agents to understand physical and digital worlds without relying on big data.

[in case you missed it] Data Science Weekly - Issue 349

Data Science Weekly Newsletter • 0 implied HN points • 02 Aug 20
🕹 Technology Data science Machine Learning Artificial Intelligence Deep Learning NLP
  1. Deep learning has important historical ideas that everyone in the field should know. Learning these basics can help new learners understand current research.
  2. As technology like GPT-3 emerges, understanding the hype around it is key. It helps to have a framework for sorting through the excitement and noise.
  3. There are challenges in using machine learning in production. It's easy to create a simple model, but making it work well with changing data is much harder.

The White House does "something" on AI

Joshua Gans' Newsletter • 0 implied HN points • 22 Jul 23
🕹 Technology AI Policy Government Research Companies
  1. The White House met with seven AI companies and they agreed to eight commitments on AI, such as internal and external security testing.
  2. Some of the commitments seem like things the companies are already doing, while others may not have a significant impact.
  3. There were some notable absences, like Apple, Tesla, and NVIDIA, from the meeting with the White House, which raises questions about the inclusivity and seriousness of the discussions.

From the Impossible to the Inevitable: AGI is Coming Faster Than You Think

Spatial Web AI by Denise Holt • 0 implied HN points • 16 Jan 23
🕹 Technology AI Neuroscience Spatial Web Artificial General Intelligence Machine Learning
  1. Active Inference and the Free Energy Principle are key concepts developed by Dr. Karl Friston for explaining how agents can maintain their internal states and behavior based on minimizing the difference between their beliefs and reality, paving the way for Artificial General Intelligence.
  2. The proposed stages of development suggest a timeline for achieving different levels of artificial intelligence, from Systemic Intelligence to Artificial Super Intelligence, showing a path towards creating more advanced AI.
  3. Active Inference AI within the Spatial Web has the potential to transform artificial intelligence into a self-evolving system that learns from real-time data, considers context, and optimizes behavior, which could lead to the realization of Artificial General Intelligence.

The AI Worries of Hollywood Actors

Joshua Gans' Newsletter • 0 implied HN points • 16 Jul 23
🕹 Technology AI Streaming Digital Media Artificial Intelligence Computer Science
  1. The Hollywood writers and actors are on strike due to concerns about how streaming services have impacted their residuals, leading to a renegotiation of contracts.
  2. The writers are worried about generative AI replacing them, leading to demands to regulate the use of AI in writing, while actors are concerned about exploitation by studios when it comes to AI usage in projects.
  3. There is uncertainty about the future impacts of AI on these professions, with a warning for writers and actors to make the most of the current situation while planning for potential career shifts.
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The Spatial Web and the Era of AI — Part 1

Spatial Web AI by Denise Holt • 0 implied HN points • 30 Dec 22
🕹 Technology AI Machine Learning Artificial Intelligence Data Analysis Web Development
  1. Deep Learning AI lacks consciousness and reasoning abilities, focusing on pattern recognition. The desire for Artificial General Intelligence requires models with 'awareness' abilities.
  2. Machine Learning AI, like GANs and Transformers, excel in specific tasks but are limited. They may lack comprehension and struggle with dynamic, real-time data.
  3. The emergence of Active Inference AI within the Spatial Web Protocol offers a roadmap to Artificial General Intelligence by enabling adaptive intelligence in a context-rich environment.

Why I am not worried about Superintelligent machines killing us all

Joshua Gans' Newsletter • 0 implied HN points • 23 Jun 23
🕹 Technology AI Superintelligence
  1. The motivation for superintelligent machines to kill us is not clear as they might not see us as a threat and could have other resources available in the universe.
  2. Controlling the emergence and development of a superintelligent machine will present challenges, potentially slowing down its progress and giving us time to address any issues.
  3. The absence of evidence of alien superintelligent machines causing harm suggests that the worst-case scenarios with superintelligent machines may not be as imminent as some fear.

Why the Spatial Web Demands a New Protocol — Part 4 — IEEE

Spatial Web AI by Denise Holt • 0 implied HN points • 15 Dec 22
🕹 Technology Internet protocols Web 3.0 Spatial Web
  1. Developing core standards for the spatial web is essential to enabling universal access, connectivity, and opportunities on a global scale.
  2. Internet protocol evolution has consistently built upon previous protocols, not replaced them, to amplify network capabilities.
  3. The IEEE, a leading technical organization, is actively involved in establishing the Hyperspace Transaction Protocol (HSTP) as a new standard for the Spatial Web (Web 3.0).

Why the Spatial Web Demands a New Protocol — Part 3

Spatial Web AI by Denise Holt • 0 implied HN points • 30 Nov 22
🕹 Technology Web 3.0 Spatial Web Artificial Intelligence Augmented reality Virtual reality
  1. Web 3.0 goes beyond Web 2.0 by creating a living, interactive world of information through technologies like AI, AR, VR, IOT, and DLT.
  2. HSML (Hyperspace Modeling Language) is crucial for understanding how objects interact in spaces based on context and for creating a technologically augmented existence.
  3. Computable context provided by HSML enables a new logic system that governs spatial elements across Smart Technologies, ensuring security, interoperability, and global collaboration in Web 3.0.

Why the Spatial Web Demands a New Protocol — Part 2

Spatial Web AI by Denise Holt • 0 implied HN points • 28 Nov 22
🕹 Technology Augmented reality Artificial Intelligence Digital Twins
  1. Web 3.0 demands a new protocol, HSTP, to handle the complexities of an augmented reality world, connecting people, places, and things in real time.
  2. HSTP and HSML enable a stateful Spatial Web, providing data ownership, zero knowledge proof technologies, and a way to search and track objects in various dimensions over time.
  3. The Spatial Web Protocol, with HSTP and HSML, creates a network of Smart Spaces, connecting physical and digital entities for a seamless, interoperable, and decentralized web experience.

Why the Spatial Web Demands a New Protocol - Part 1

Spatial Web AI by Denise Holt • 0 implied HN points • 16 Nov 22
🕹 Technology Web Development Networking Artificial Intelligence Virtual reality Internet of Things
  1. Technology naturally expands and sophisticates over time, driven by human curiosity and the Law of Accelerating Returns
  2. Computing has evolved through various stages, adding layers for increased capabilities, like AI, blockchain, and AR/VR
  3. The Spatial Web introduces new protocols (HSTP and HSML) to accommodate the growth in technology, enhancing collaboration and interaction in complex network computing

Apple's Big Experiment

Joshua Gans' Newsletter • 0 implied HN points • 06 Jun 23
🕹 Technology AI Virtual reality Augmented reality Artificial Intelligence User Interface
  1. Apple's new Vision Pro device is heavily powered by AI, despite Apple not explicitly mentioning AI in its marketing. The device uses AI for interactions, user interface, latency reduction, and even predicting user behavior.
  2. Apple's approach with the Vision Pro is a 'best foot forward' experiment, focusing on creating a functional and user-friendly spatial computer. The success or failure of this experiment could impact the future of AR and VR technology development.
  3. The Vision Pro's high price tag of $3,499 positions it as a premium product, akin to Apple's previous pricey but successful launches like the original iPhone. The device's success may determine the future of AR and VR investments in the tech industry.

WWW vs. The Spatial Web

Spatial Web AI by Denise Holt • 0 implied HN points • 18 Oct 22
🕹 Technology Web Internet Metaverse Digital Twins Spatial Web
  1. The Spatial Web is a new approach to networking spaces and objects, connecting real and virtual elements together.
  2. The internet, specifically the World Wide Web, has evolved from connecting computers with slow connections to dynamic web pages and now faces limitations with merging physical and digital experiences.
  3. The Spatial Web introduces a Stateful system with data sovereignty, allowing users to control and own their data interactions within various spaces and circumstances.

They say AI is going to be the End of Us ... Again

Joshua Gans' Newsletter • 0 implied HN points • 30 May 23
🕹 Technology AI Risk Existential Ethics
  1. Some AI experts have raised concerns about the risks associated with AI, emphasizing the need to prioritize mitigating these risks alongside other existential threats like pandemics and nuclear war.
  2. The statement by the experts has sparked discussions on whether allocating resources to mitigating AI risks should be as high of a priority as addressing other more immediate and evident threats.
  3. While acknowledging the importance of considering AI existential risks, the argument is made that currently, these risks are still largely hypothetical and should be approached with caution in terms of resource allocation.

The Spatial Web is Coming — Part 4

Spatial Web AI by Denise Holt • 0 implied HN points • 13 Oct 22
🕹 Technology Web 3.0 Spatial Web Blockchain AI
  1. Web 3.0 envisions a common network where everything is connected, blurring the line between the physical and digital worlds.
  2. The future Web 3.0 will involve a fully networked interface, powered by advanced technology like KOSM AI.
  3. To stay relevant in the future Web 3.0, companies and individuals must be part of this all-encompassing network of everything.

The Spatial Web is Coming — Part 2

Spatial Web AI by Denise Holt • 0 implied HN points • 11 Oct 22
🕹 Technology AR VR AI IOT
  1. The Spatial Web integrates AR, VR, AI, IOT, and Distributed Ledger innovation to blend real and virtual worlds.
  2. Smart Technologies include Smart Spaces, Smart Assets, Smart Contracts, Smart Accounts, Smart IDs, and Smart Payments.
  3. These technologies enable programmable spaces, ownership verification, secure transactions, self-sovereign identity, and automated payments in the Web 3.0 ecosystem.

Learning about Estonia's Digital Society

Joshua Gans' Newsletter • 0 implied HN points • 22 May 23
🕹 Technology Digital Society Start-ups Cybersecurity Information Management
  1. Estonia leads the world in having the most $1 billion-plus valued start-ups per capita, showcasing a thriving entrepreneurial ecosystem.
  2. Estonia has achieved an outstanding digital society, with a government that operates paperlessly and based on the principle of entering information only once, setting a new standard for efficiency and convenience.
  3. The success of Estonia's digital transformation was not immediately evident in the physical environment, highlighting the importance of deliberate legal and political decisions driving technological advancements.

Are Acemoglu and Johnson right about AI?

Joshua Gans' Newsletter • 0 implied HN points • 19 May 23
🕹 Technology AI Economics Automation Productivity Innovation
  1. Acemoglu and Johnson discuss how power in the economy is determined by persuasion and political institutions, not just by economic forces. They stress the importance of understanding and addressing these power dynamics.
  2. The authors argue that technology, including AI, is not predetermined to drive inequality; instead, it depends on the choices made by companies and powerful actors. This challenges the idea of inevitable inequality due to technological advancement.
  3. Acemoglu and Johnson express concerns about AI automation potentially leading to the loss of valuable human skills and expertise, emphasizing the importance of considering the long-term impacts of AI adoption. They caution against short-term views on worker contributions.

The Spatial Web is Coming — Part 1

Spatial Web AI by Denise Holt • 0 implied HN points • 10 Oct 22
🕹 Technology AI AR VR IOT Blockchain
  1. The Spatial Web involves the convergence of technologies like AR, VR, AI, and IoT in a unified network for a seamless experience.
  2. Many Web3 technologies lack a common language protocol, causing them to be isolated and not fully interconnected.
  3. For the future Spatial Web browsing experience, a unique protocol like HSTP is needed to connect physical and virtual entities for a smarter, more integrated world.

Coming soon

Slalom dev blog • 0 implied HN points • 08 Feb 24
🕹 Technology Blogging
  1. The blog is coming soon on slalomlang.substack.com
  2. The post was shared multiple times on different platforms like Facebook and email
  3. The blog seems to focus on Slalom development

Are Acemoglu and Johnson right about AI?

Joshua Gans' Newsletter • 0 implied HN points • 19 May 23
🕹 Technology AI Automation Productivity AI adoption
  1. Daron Acemoglu and Simon Johnson's book 'Power and Progress' delves into power dynamics in economics, emphasizing the role of political institutions in shaping economic value distribution.
  2. Acemoglu and Johnson present a view on AI automation, suggesting that AI replicated human tasks but does not offer significant productivity gains. They express concerns about automation leading to job loss without substantial benefits.
  3. Contrary to Acemoglu and Johnson's view, it's argued that AI can bring massive productivity improvements and that current AI adoption signifies significant advancements. The book's projections about AI's negative impacts are viewed with skepticism.

The discourse about AI is weirdly terrible

Joshua Gans' Newsletter • 0 implied HN points • 08 May 23
🕹 Technology AI Regulation Market Capitalism Automation
  1. The debate on AI lacks economics and is often polarized and unproductive.
  2. The core of the AI discussion is essentially about regulation, where uncertainty should be acknowledged and addressed through experimentation.
  3. Wealthy individuals, despite their usual stance against regulation, are concerned about AI's potential power and advocate for regulation to potentially prevent threats to their status quo.

A meeting that could have been automated

Joshua Gans' Newsletter • 0 implied HN points • 20 Apr 23
🕹 Technology Artificial Intelligence Automation Communication
  1. Meetings can be productive but come with costs like time and dissatisfaction. Despite this, they are essential for organizations to align and move forward.
  2. AI is being used to automate communication tasks like summarizing documents or transcribing meetings. This can save time and make processes more efficient.
  3. The idea of using AI chatbots to attend meetings on behalf of individuals is a creative automation solution. It could potentially revolutionize the way meetings are conducted, making them more efficient and less time-consuming.

I picked a bad day to restart my substack

Joshua Gans' Newsletter • 0 implied HN points • 08 Apr 23
🕹 Technology Innovation Entrepreneurship Social media Digital Platforms Artificial Intelligence
  1. The newsletter 'Mess and Magic' is being relaunched by Joshua Gans, focusing on the economics of innovation, entrepreneurship, and technology, particularly artificial intelligence.
  2. Twitter broke interactions with Substack, which impacts the ability to share links and discuss newsletters on the platform.
  3. There are speculations about Twitter's motives for breaking links with Substack, potentially related to competition and attracting users to their platform instead.

July 2021 Tech Buzz China Newsletter

Tech Buzz China Insider • 0 implied HN points • 08 Dec 21
🕹 Technology News Podcasts Business China Social media
  1. Tech Buzz China has launched a Livecast series where they interact with China tech investors, entrepreneurs, and practitioners, providing an open platform for engaging discussions and insights.
  2. The Tech Buzz China Insider is a premium community offering in-depth analyses of China tech, catering to investors and operators interested in exclusive content not widely available in English media.
  3. Tech Buzz China has been featured in various media outlets, showcasing their expertise and insights on China tech developments, anti-monopoly enforcements, social commerce, and more.

[in case you missed it] Data Science Weekly - Issue 362

Data Science Weekly Newsletter • 0 implied HN points • 01 Nov 20
🕹 Technology Data science Machine Learning Artificial Intelligence Software Engineering Analytics
  1. Using AI for form extraction can greatly help fields like journalism and medicine. This could be more impactful than just predictive models.
  2. Data intuition is an important skill for data scientists. It helps them avoid being misled by bad data and analyses.
  3. Data engineering and data science are interconnected, but they have different focuses. Data engineering deals with preparing data, while data science analyzes it for insights.

[in case you missed it] Data Science Weekly - Issue 366

Data Science Weekly Newsletter • 0 implied HN points • 29 Nov 20
🕹 Technology Data science Machine Learning AI Software Engineering Data Analysis
  1. Pinterest improved its data infrastructure by moving from Lambda to Kappa architecture to better handle its visual signals for machine learning. This change aimed to streamline costs and enhance signal availability.
  2. When building machine learning models, companies like DoorDash face huge data challenges. Choosing the right feature store is crucial for managing this data effectively, ensuring performance without overspending.
  3. Differentially private learning still faces challenges in performance compared to traditional models. For effective results, more private data or improved features from public data may be necessary.

That's some BS

Links I Would Gchat You If We Were Friends • 0 implied HN points • 29 Sep 15
🕹 Technology Social media Politics Smartphones Machine Learning Internet
  1. The concept of 'personal brand' can be perceived as privileged and self-important, especially in a competitive market.
  2. There are 'neoreactionaries' on the internet who oppose democracy and predict a future led by the far right.
  3. Apple products like iPhones may have biases, like being more right-hander oriented, which can be frustrating for left-handed users.

[in case you missed it] Data Science Weekly - Issue 371

Data Science Weekly Newsletter • 0 implied HN points • 03 Jan 21
🕹 Technology Machine Learning Data science AI Tools Statistical Methods Programming
  1. Real-time machine learning is becoming important for many companies, with some investing heavily in the necessary infrastructure. This has led to positive financial returns for them.
  2. There is a growing list of tools for machine learning operations, with many new entries improving how developers can manage their ML projects.
  3. Different techniques like Markov models can help in planning and optimizing tasks, like workout routines, by predicting the next steps based on previous actions.

Oberon International's Omni-Reader

Computer Ads from the Past • 0 implied HN points • 17 Dec 24
🕹 Technology Computers History Engineering
  1. The Omni-Reader is a tool designed to make data entry easier by using optical character recognition (OCR) technology. It helps users scan printed text and input it into their computers without having to type everything manually.
  2. Despite its potential, the Omni-Reader has limitations. It can struggle with different types of text quality and formatting, making it less reliable for certain tasks.
  3. Oberon International, the company behind the Omni-Reader, aimed to provide a low-cost solution for OCR, but it had issues that made it more suitable for occasional use rather than frequent office work.

[in case you missed it] Data Science Weekly - Issue 376

Data Science Weekly Newsletter • 0 implied HN points • 07 Feb 21
🕹 Technology Data science Machine Learning Artificial Intelligence Statistics Software Development
  1. Data quality is really important in high-stakes AI because it can greatly affect results in areas like health and finance. Many people focus on building models instead of ensuring good data quality.
  2. DanNet was a game-changer in computer vision when it was released ten years ago. It showed that deep learning models could even surpass human performance in certain tasks.
  3. Cohort analysis helps businesses understand their customers better by tracking different groups over time. It's useful for figuring out things like customer engagement and product performance.

[in case you missed it] Data Science Weekly - Issue 378

Data Science Weekly Newsletter • 0 implied HN points • 21 Feb 21
🕹 Technology Data science Machine Learning Artificial Intelligence Data Analytics Software Development
  1. Creating robots that can think morally is similar to parenting. Teaching them right from wrong can be approached in the same way we teach children.
  2. Transformers are important in both language and image processing. Understanding how to use them can help with many tasks in data science.
  3. Building systems for data quality and observability is essential. By using tools like SQL, we can keep track of how our data changes and ensure it stays reliable.

We'll never let go, until we do

Links I Would Gchat You If We Were Friends • 0 implied HN points • 29 Feb 16
🕹 Technology Privacy Bias Tech influence Memes Artificial Intelligence
  1. The FBI wants access to our minds, not just our phones, according to the 'extended mind hypothesis.'
  2. Netflix recommendations show racial biases - defaulting to 'white' movies until you indicate preference for diversity.
  3. Mark Zuckerberg's grey T-shirt uniform is an unexpected lifestyle choice, suggesting simplicity and consistency.

[in case you missed it] Data Science Weekly - Issue 379

Data Science Weekly Newsletter • 0 implied HN points • 28 Feb 21
🕹 Technology Data science Machine Learning Artificial Intelligence Software Engineering Programming
  1. Writing a book about data science can be a fun way to share knowledge and inspire others. It's also possible to make money online while doing it.
  2. Understanding Python concurrency is important for data scientists. Learning about topics like async and threads can boost your software engineering skills.
  3. Feature stores are essential for operationalizing machine learning. They help teams manage and deploy machine learning features efficiently.

[in case you missed it] Data Science Weekly - Issue 382

Data Science Weekly Newsletter • 0 implied HN points • 21 Mar 21
🕹 Technology Data science AI Machine Learning Statistics Visualization
  1. Computers can't write good stories. It's a big claim, but they really don't understand literature like humans do.
  2. Using color scales is important when showing data visually. Choosing the right colors can make your data easier to understand.
  3. Data science can help fight illegal fishing with satellite data. By tracking boats, experts can prevent unlawful activities in our oceans.

[in case you missed it] Data Science Weekly - Issue 387

Data Science Weekly Newsletter • 0 implied HN points • 25 Apr 21
🕹 Technology Data science Machine Learning Artificial Intelligence Computer Science Software Engineering
  1. Goodreads lets users decide what counts as a classic book, showing how the definition has changed over time. This online platform helps readers share their thoughts in various ways.
  2. Scientists are trying to decode whale language using AI, aiming to understand how these marine animals communicate. This research could reveal insights about their behavior and society.
  3. New techniques allow neural networks to solve tough equations much faster. This improvement can help us better model complex systems, making it easier for researchers and engineers.

[in case you missed it] Data Science Weekly - Issue 388

Data Science Weekly Newsletter • 0 implied HN points • 02 May 21
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization
  1. Cluster analysis can be tricky since you often don't know how many groups to create. A new method called clustergram helps visualize data better as you adjust the number of clusters.
  2. Bayesian and frequentist methods in statistics provide different types of results, so they shouldn't be compared directly. They answer different questions rather than yielding similar outputs.
  3. Netflix is working on a feature called 'Play Something' to combat decision fatigue. This feature plays a show automatically, similar to turning on a TV, making it easier for users to start watching.

OFF my lawn

Links I Would Gchat You If We Were Friends • 0 implied HN points • 17 Mar 16
🕹 Technology Internet Art Computer Science
  1. Garbage person insult originates from Manson's self-reference during trial, now widely used online for various situations.
  2. The internet is transforming discussions in the art world towards shallowness and democracy, seen in literature and other creative fields.
  3. Humans created the computer program that beat humans at the game of Go, showcasing the complexity at the intersection of strategy games and computer science.