The hottest AI Applications Substack posts right now

And their main takeaways
Category
Top Technology Topics

As AI Hits E-Discovery, Lawyers Move From Biglaw To A Boutique

Original Jurisdiction • 219 implied HN points • 24 Oct 24
💼 Business Technology AI Applications
  1. E-discovery is becoming more complex due to the vast amount of data from various digital sources, leading lawyers to specialize more in this area.
  2. Boutique law firms like Redgrave focus only on e-discovery, allowing them to handle cases more efficiently than larger firms.
  3. Generative AI is changing e-discovery by making it faster and more effective, but it also brings challenges like ensuring document authenticity and managing privacy laws.

Doctors Won't Listen. Is Artificial Intelligence the Answer?

COVID Reason • 356 implied HN points • 02 Oct 24
🏥 Health Politics Medical Ethics Healthcare policy Technology Integration AI Applications Patient Care
  1. The COVID-19 pandemic revealed flaws in the healthcare system, showing that some doctors may not always listen to their patients or critically evaluate their practices.
  2. A study found that while AI like GPT-4 can diagnose accurately on its own, doctors did not significantly improve their performance using it, possibly due to skepticism and integration issues.
  3. For AI to be effective in healthcare, there needs to be better collaboration between doctors and AI tools, focusing on trust and finding ways to integrate AI smoothly into their work.

Is the AI Boom Real?

The Asianometry Newsletter • 3553 implied HN points • 07 Mar 24
🕹 Technology AI Semiconductors Tech Giants Financial sustainability AI Applications
  1. The trillion-dollar investment in AI chips does raise skepticism, with questions about its sustainability and impact on the semiconductor industry.
  2. The concept of scaling laws, driving investments, presents interesting parallels to Moore's Law in the semiconductor industry, suggesting potential future impact on AI.
  3. Competition in AI chips, particularly against Nvidia, is heating up as tech giants aim for vertical integration, potentially shifting the landscape of AI chip design and market dynamics.

AI Agents: Exploring Agentic Applications

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 119 implied HN points • 29 Jul 24
🕹 Technology AI Applications Machine Learning Natural Language Data Tools
  1. Agentic applications are AI systems that can perform tasks and make decisions on their own, using advanced models. They can adapt their actions based on user input and the environment.
  2. OpenAgents is a platform designed to help regular users interact with AI agents easily. It includes different types of agents for data analysis, web browsing, and integrating daily tools.
  3. For these AI agents to work well, they need to be user-friendly, quick, and handle mistakes gracefully. This is important to ensure that everyone can use them, not just tech experts.

Rox

Not Boring by Packy McCormick • 152 implied HN points • 26 Nov 24
💼 Business Startups AI Applications Sales Strategy Technology Integration
  1. Rox is creating a new kind of CRM that's built around AI. They want to help salespeople work better by giving them smart tools that can handle data quickly and effectively.
  2. AI won't replace all sales jobs, but it will make the best salespeople even better. The goal is to help strong sellers do their job more efficiently, not to take their roles away.
  3. Rox is focused on getting companies to connect their data to their system. By doing this, they can become a key part of how those companies operate, leading to better sales results.
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471: Relative Valuation, Perplexity AI, RIP Artifact, Hertz Sells Teslas, Marc Andreessen, DARPA Plane, Uranium, LEDs, and Jake Gyllenhaal

Liberty’s Highlights • 1041 implied HN points • 17 Jan 24
🕹 Technology AI Electric Vehicles AI Applications Renewable Energy Aerospace
  1. Opportunity cost is often invisible but significant, so consider it in decision-making.
  2. Relative valuation in investing can be misleading, so always dig deeper.
  3. Mixing children of different ages in schools could offer benefits in learning and social development.

Artificial Intelligence: Mastercard’s new Neural Network for enhanced fraud detection

The Fintech Blueprint • 452 implied HN points • 06 Feb 24
🕹 Technology Artificial Intelligence Finance Deepfakes AI Applications
  1. Annual card fraud exceeds $33B, with digital wallets, credit, and debit cards projected to handle 86% of global POS payments by 2026.
  2. Mastercard introduced a new AI model, Digital Intelligence Pro, to improve fraud detection by using a proprietary recurrent neural network.
  3. Digital Intelligence Pro aims to reduce false positive fraud flags, leading to better fraud detection rates, potential savings of $90B yearly for merchants, and improved customer experiences.

Joyspan, Emotional AI Bumpers, Persona Designers, & More Wild Concepts Bound to Become Commonplace Plus Where High-Tech Entertainment Brings Us

Implications, by Scott Belsky • 471 implied HN points • 19 Dec 23
🕹 Technology Artificial Intelligence Entertainment Digital Experiences AI Applications Future Technology
  1. Society evolves as wild concepts become mainstream, like connected appliances and AI-powered persona designers.
  2. The future of entertainment will focus on shared, authentic, non-scalable experiences over high-tech extravagance.
  3. Scarcity and authenticity will be essential in the next wave of digital experiences, emphasizing uniqueness and community connections.

Import AI 334: Better distillation; the UK's AI taskforce; money and AI

Import AI • 399 implied HN points • 10 Jul 23
🕹 Technology AI Research Generative models Funding AI Applications
  1. DeepMind developed Generalized Knowledge Distillation to make large models cheaper and more portable without losing performance.
  2. The UK's £100 million Foundation Model Taskforce aims to shape the future of safe AI and will host a global summit on AI.
  3. Significant financial investments in AI, like Databricks acquiring MosaicML for $1.3 billion, indicate growing strategic importance of AI in various sectors.

KSDRP: Settling Science Fairly. A new method to objectively resolve scientific disputes

Steve Kirsch's newsletter • 3 implied HN points • 22 May 25
🔬 Science Scientific Method Data Analysis AI Applications Health Science Public Debate
  1. The Kirsch Scientific Dispute Resolution Protocol (KSDRP) is a new way to settle scientific disagreements logically and fairly.
  2. It involves choosing judges, using real data, and letting chatbots help analyze the information before judges make a final decision.
  3. This method can help answer tough questions, like the impact of COVID vaccines, by measuring outcomes from different groups.

AI's missing middle

The Uncertainty Mindset (soon to become tbd) • 2 HN points • 18 Sep 24
🕹 Technology AI Applications Startups Business Processes
  1. There is a big opportunity for AI startups to create tools specifically for medium-sized businesses in traditional industries. These businesses could greatly benefit from AI solutions that fit into their existing processes.
  2. Many current AI startups focus on becoming major companies but ignore the needs of smaller markets. By targeting medium-sized firms, startups can develop practical AI applications that have immediate positive impacts.
  3. To succeed, startups need better funding and industry knowledge. Creating focused incubators could help bridge these gaps, allowing more startups to thrive and innovate in the AI space for medium-sized businesses.

UX Roundup: Jakob Keynote Video | University Courses | 8 Uses of AI for UX Design | Museum Usability

Jakob Nielsen on UX • 32 implied HN points • 18 Nov 24
🕹 Technology UX Design AI Applications User Research
  1. AI is becoming a major force in UX design, helping teams work faster and more efficiently. It's taking over mundane tasks, allowing designers to focus on more important work.
  2. Educational programs are starting to include AI in their UX courses, preparing future designers for the changing landscape of the industry. This is a positive step for those looking to enter the field.
  3. Good usability in places like museums can greatly improve visitor experience. Clear signage and easy navigation are key factors in making sure everyone enjoys their visit.

Decoding Apple's AI Ambitions

Gradient Flow • 219 implied HN points • 29 Jun 23
🕹 Technology Artificial Intelligence Machine Learning Data processing AI Applications Data Management
  1. Apple's AI focus is on Machine Learning and Computer Vision with emerging areas like Robotics and Speech Recognition, aiming to enhance services like Siri.
  2. Apple shows active interest in AI areas like Generative AI and large language models through their job postings, emphasizing deep learning skills.
  3. Apple's AI strategy integrates hardware and software to provide personalized experiences, leveraging silicon chips, Neural Engine, and fine-grained data for future AI applications.

Last Week in AI #248: ChatGPT's 1st birthday, Amazon's new AI chatbot Q, the energy cost of generative AI, Sam Altman makes statement after return, and more!

Last Week in AI • 178 implied HN points • 04 Dec 23
🕹 Technology AI Chatbots Leadership Changes AI Applications
  1. ChatGPT has made a significant impact in the past year with its interactive and conversational dialogue capabilities
  2. Amazon's new AI chatbot Q for companies has faced reliability issues, including hallucinations and data exposure during its public preview
  3. Generative AI, like image generation, consumes significant energy, equivalent to charging a smartphone, prompting a need to consider the environmental impact of AI technologies

From Rockets to Roadmaps: An Engineer's Guide to Product Success

Dev Interrupted • 14 implied HN points • 03 Dec 24
🕹 Technology Software Development Engineering Culture AI Applications Product Management Team Dynamics
  1. Engineers can drive product vision, leading to faster and more innovative development. This shifts the focus from just coding to solving real business problems.
  2. With AI making coding easier, engineers who understand customer needs and market trends will stand out. Their blend of technical skills and business savvy is crucial for success.
  3. Collaboration and teamwork are key in software development. It's not just about individual contributions but how teams work together to create better solutions.

How to Earn Extra $15000 from GenAI

Sector 6 | The Newsletter of AIM • 19 implied HN points • 03 Jul 24
💼 Business Entrepreneurship Marketing Finance AI Applications
  1. You can use tools like ChatGPT and Canva to potentially earn extra money each month. These tools help with tasks such as designing products and creating advertisements.
  2. Some people promote courses or guides that claim you can get rich quickly with AI. But many times, these are just advertisements and not very helpful.
  3. There are practical ways to use AI tools for small jobs, like making designs for social media or videos, which can lead to extra income.

The Tech Buffet #22: Why You Should Consider Weaviate As Your Ultimate Vector Database

The Tech Buffet • 39 implied HN points • 23 Apr 24
🕹 Technology Machine Learning Data science Software Development Database Management AI Applications
  1. Weaviate is a powerful vector database that helps in creating advanced AI applications. It's useful for managing large amounts of data and performing semantic searches efficiently.
  2. When working with Weaviate, you can easily load and index data, allowing for quick access to information. This makes it easier to build systems that need to handle a lot of data quickly.
  3. Weaviate supports different search methods like vector search, keyword search, and hybrid search. This way, you can find the most relevant results based on your needs.

💸 The Hidden Cost of Context Switching

ppdispatch • 11 implied HN points • 11 Feb 25
🕹 Technology Software Development AI Applications Productivity Tools Data Management Legal issues
  1. Frequent interruptions, even from short messages, can hurt developers' productivity a lot. It can take over 20 minutes to refocus after just one distraction.
  2. A small update to the Linux kernel can really boost data center efficiency, potentially cutting power use by 30%. This change helps manage network traffic better without needing much setup.
  3. Many math libraries don't follow floating-point standards, leading to rounding errors. This can cause big problems in areas like gaming and machine learning where precision is key.

Groq, Gemini, and 10x improvements

Artificial Ignorance • 67 implied HN points • 21 Feb 24
🕹 Technology AI Chips Software AI Applications
  1. Adding 10x capacity to a system unlocks new capabilities and prevents breaking, leading to fundamental changes.
  2. Gemini 1.5's 10x larger context window enables tasks like analyzing entire codebases, filtering massive datasets, and potentially building AI with better memory.
  3. Groq's custom AI chips achieve lightning-fast token generation, paving the way for real-time AI conversations, enhanced data handling, and possible use in finance, medicine, and robotics.

Natural Language Is an Unnatural Interface

Public Experiments • 154 HN points • 27 Jun 23
🕹 Technology AI Interfaces Natural Language Processing AI Applications Open-source models
  1. Natural language interfaces for AI are challenging due to the vast degree of freedom in text input.
  2. Prompt engineering is crucial for effectively utilizing large language models to ensure correct and meaningful responses.
  3. For most users, interacting with AI systems through buttons and defined interfaces can lead to more efficient and seamless experiences compared to using natural language prompts.

AI Roundup 053: Bye bye Bard

Artificial Ignorance • 54 implied HN points • 09 Feb 24
🕹 Technology AI Deepfakes Regulation Tech Companies AI Applications
  1. Google rebrands AI product line Bard to Gemini, introducing multiple tiers including a paid plan powered by Gemini Ultra.
  2. Initiatives like the C2PA aim to address deepfake content issues, with companies like Google and OpenAI joining efforts for content authentication.
  3. FCC deems robocalls with fake AI-created voices as illegal, showcasing government agencies taking action on AI regulation independently.

ChatGPT can predict analyst forecast changes

Klement on Investing • 4 implied HN points • 19 Nov 24
💰 Finance Investing AI Applications Market Trends Performance analysis
  1. ChatGPT can analyze earnings calls and predict how analysts will change their forecasts. This means it can assess important company factors like growth and risk.
  2. The Analyst Insight Score (AIS) created from ChatGPT's analysis is better at predicting analyst actions and stock prices than traditional methods. It's about two to four times more effective.
  3. There's concern that as AI like ChatGPT improves in its analysis, it might replace human jobs in finance. This includes roles like equity analysts and fund managers.

Giving GPT "Infinite" Knowledge

Sudo Apps • 121 HN points • 06 May 23
🕹 Technology Data processing Machine Learning AI Applications Real-Time Data
  1. Training Large Language Models (LLMs) with new data constantly is impractical due to the vast amount of information and privacy concerns.
  2. OpenAI's focus on improving LLMs in other ways instead of just increasing model size indicates the end of giant model era.
  3. Using tokens, embeddings, vector storage, and prompting can help provide LLMs with large amounts of data for better interpretation and understanding.

AI Roundup 056: Data deals

Artificial Ignorance • 42 implied HN points • 01 Mar 24
🕹 Technology AI AI Applications
  1. User-generated content companies are capitalizing on the value of their posts and comments by offering them through licensing regimes.
  2. Tech giants like Google, Apple, Microsoft, and others are heavily investing in AI initiatives and tools to advance various industries.
  3. AI advancements are causing concerns regarding bias, safety, and potential misuse in areas like diverse data deals, model releases, and deepfakes.

ML Data Labeling Tools Structure Information to Make It Meaningful - Market Map and Analysis

The Strategy Deck • 39 implied HN points • 17 Jul 23
🕹 Technology Computer Vision AI Applications
  1. Data labeling is crucial for improving the quality of ML models by adding meaningful labels.
  2. Data labeling tools offer features like support for various data types, collaboration between annotators, and data versioning.
  3. ML platforms for data labeling include multi-modal, general purpose tools for manual labeling and programmatic tools focusing on specific data types and niches.

Embed Retrieve Win

Gradient Flow • 99 implied HN points • 29 Sep 22
🕹 Technology Machine Learning Data Infrastructure Generative models NLP AI Applications
  1. Embeddings are low-dimensional spaces that make AI applications faster and cheaper while maintaining quality.
  2. Vector databases are designed for vector embeddings and are becoming essential for modern search engines and recommendation systems.
  3. Generative models like diffusion models are gaining attention in the research community and offer great opportunities for exploration and innovative projects.

Brand Safe AI

Addition • 19 implied HN points • 07 Jun 23
🕹 Technology AI Design Risk mitigation Safety AI Applications
  1. Brand safety in AI is not a one-size-fits-all concept; it varies based on the specific use case and how AI is implemented.
  2. Design decisions play a crucial role in aligning the level of risk in an AI system with what the organization is willing to accept.
  3. Addressing brand safety creatively involves different approaches like incorporating safety checks, narrow use cases, and extensive testing to mitigate risks.

Experimentation Tools; Surge in MLOps; 2021 Books

Gradient Flow • 39 implied HN points • 09 Dec 21
🕹 Technology Data Infrastructure Machine Learning AI Applications Books Podcasts
  1. Investors and engineers are focusing on ML infrastructure and MLOps, but experimentation tools need more attention to bridge the gap between data teams and product teams.
  2. Financial services industry is utilizing AI and NLP via no-code platforms to build and deploy applications.
  3. Recommendations of books include topics on cyberweapons, macroeconomics, venture capital, and predictive investment frameworks.

AI is Revolutionizing Search but Also Bringing a Major Problem

Jeff’s Substack • 1 HN point • 29 Mar 24
🕹 Technology AI Search Engines Content Generation Tech Companies AI Applications
  1. Artificial intelligence is changing the way we search for information by providing direct answers instead of links, decreasing reliance on traditional search methods.
  2. AI-generated content is abundant online but varies in quality, affecting the usefulness of search results and potentially disrupting the balance between publishers, tech giants, and advertisers.
  3. The rise of AI tools like GPT-4 and platforms like Reddit faces challenges and changes traditional online interactions and communities, leading to shifts in websites and businesses.

How To Price A Data Asset

Pivotal • 2 HN points • 11 May 24
💼 Business Market Strategies AI Applications
  1. Data has no inherent value; its worth depends on how it's used and by whom. Different users will find different values in the same dataset.
  2. The pricing of data isn't straightforward; it involves understanding the uniqueness and quality of the data, its lifecycle, and the specific needs of users.
  3. As AI continues to grow, the demand for data is changing, with more emphasis on quantity over quality. This shift makes understanding how to price data assets increasingly important.

Where Are the Good AI Products?

Public Experiments • 2 HN points • 16 Feb 24
🕹 Technology AI Software Engineering Startups Future of work AI Applications
  1. Many people have yet to experience the impact of AI in their daily lives, indicating that the anticipated AI-driven future is not fully realized yet.
  2. AI tools like ChatGPT and Copilot are currently used by individuals but haven't proliferated widely, with some potential hurdles being the need for broader education and the slow pace of product innovation.
  3. The future of AI products may unfold slowly over the next 5-10 years, with challenges like technical limitations, business viability, and the need for transformative breakthroughs still to be addressed.

What is Mojo Programming Language?

Machine Economy Press • 3 implied HN points • 04 May 23
🕹 Technology Programming AI Development AI Applications
  1. Mojo Programming Language combines Python syntax with the speed of C, making it ideal for AI development.
  2. Mojo is about 35,000 times faster than Python, offering exceptional AI hardware programmability and model extensibility.
  3. Mojo allows writing portable code faster than C, seamlessly inter-operating with the Python ecosystem, and includes features like a unified inference engine and zero-cost abstractions.