Francisco Dalla Rosa Soares

One interesting thing about Deepseek, according to its company CEO Liang Wenfeng, is that unlike many Chinese AI companies, they didn’t just copy Llama & tweak a few things, they innovated on a new architecture which allowed them to achieve these prices. Interview linked below.

7

1件のコメント

Aide is on the HN frontpage 🎉 If you are still wondering or on the fence for an AI native editor check out Aide! - A proactive agent 🧠 Agent which iterates on the linter errors (powered by the Language Server) and pulls in relevant context by doing go-to-definitions, go-to-references etc and propose fixes or ask for more files which might be missing in the context. - Developer control 🎛️ We encourage you to do edits on top of your coding sessions. To enable this, we built a VSCode native rollback feature which gets rid of all the edits made by the agent in a single click if there were mistakes, without messing up your changes from before. - A combined chat+edit flow which you can use to brainstorm and edit 🎮 You can brainstorm a problem in chat by @’ting the files and then jump into edits (which can happen across multiple files) or go from a smaller set of edits and discuss the side-effects of it - Inline editing widget 🛼 We took inspiration from the macos spotlight widget and created a similar one inside the editor, you can highlight part of the code, do Cmd+K and just give your instructions freely - Local running AI brain 👾 We ship a binary called sidecar which takes care of talking to the LLM providers, preparing the prompts and using the editor for the LLM. All of this is local first and you get full control over the prompts/responses without anything leaking to our end (unless you choose to use your subscription and share the data with us) You can try out aide by visiting our website: https://aide.dev/ and if you don't find the right binary grab it from here: https://lnkd.in/dENhT_Tc

58

2件のコメント

Earlier this year, Jensen Huang - Founder / CEO of Nvidia - opined the following when asked where he thought the next amazing revolution was going to come from: - (Text transcribed verbatim) ***************** "This is going to be flat out one of the biggest ones ever, and I told you I was going to tell you, and I'm going to tell you. There's no question that digital biology is going to be it. For the very first time in our history, in human history, biology has the opportunity to be engineering, not science. When something becomes engineering, not science, it becomes less sporadic and exponentially improving. It can compound on the benefits of the previous years, and every company's contributions, every research's contributions, compound on each other. For the very first time, we know how to represent biology, understand the language of biology. We can represent the language of chemistry. It's never happened before. And now we're going to have incredible tools that bring the world of biology, which is very chaotic and constantly changing, and very diverse and complex, and bring it into the world of computer science. And that is going to be profound. And so if you happen to love this intersection, I think it's going to be rich with opportunities. It's going to be a giant industry." ***************** Now if you take this thesis and apply it to the world of #ClinicalDevelopment / #ClinDev in #LifeSciences, the opportunities to leverage #AI cuts across: * optimizing trial design * patient recruitment and retention * data analysis and prediction And the impact on the speed, cost, and efficacy of new therapeutics will be profound. And so I am really looking forward to joining some of the best minds in the intersection of AI and Life Sciences including Adam Petrich, MD | Arnaub Chatterjee | Prof Ava Amini from MSFT | Charbel Haber from Moderna | Fred Martin | Ittai Harel | Thaminda Ramanayake | Jasmine LaCoursiere | Gaurav Singal, MD former Chief Data Officer from Foundation Medicine | Orr Inbar | Sean Hilscher | Thorsten Wirkes from Bertlessman at the world's first AI Summit focused on clinical development in Boston on May 30th. Together we hope to demystify the role of AI in Clinical Development, discuss the risks and regulatory issues surrounding this field, and real-world applications and success stories, and the venture capital investment happening in this area. Apply to join us on May 30th - https://qhsummit24.com/

75

9件のコメント

Looking forward to my second #ProductTO, I am excited to go back as a facilitator this time, discussing one of my favourite topics: #AI and #ProductManagement, obviously we will scope it down to a specific topic! Here is my experience from last month's event: https://lnkd.in/g_V7kb3Y I highly recommend joining this community! The event format is different, allowing meaningful discussions and connection building! #ProductManagement #Canada #Toronto #Learning

8

LLM without access to your latest data is like a genius who’s been living under a rock for years. RAG is the solution: Learn how Airbnb is getting best out of LLMs by augmenting it with their data using RAG, embeddings and Vector Datastore. In the video Moutupsi Paul Xiaotang Wang and I diving deep into Airbnb comprehensive Embedding Platform that can support multiple use cases such as image search. You will Learn why OpenSearch and LLMs are better together and how to get most value with OpenSearch. Kudos and Thanks to the awesome people at Airbnb and OpenSearch Project to make this possible. Henry Saputra Tomas F. Yangbo Zhu Soumyadip Banerjee Mukul Karnik Carl Meadows Jon Handler Pavani Garimella Baddepudi Vamshi Vijay Nakkirtha Bob Taylor Parth Shah Ritz H. Mikhail Smelik Madhuri Peri JC Lima Lauren Larscheid #AI #LLM #OpenSearch #Airbnb #GenAI

46

1件のコメント

🗝️ Need Skyvern to log into websites with TOTPs? Don't worry -- we've got you covered! We already supported QR-code based TOTPs, but email / SMS based TOTPs were the bane of our existence.. until Shuchang Zheng stepped in. Shuchang Zheng just launched a killer feature: TOTPs within Skyvern. You can now give Skyvern a TOTP retrieval URL, and when Skyvern is presented with a screen asking for a 2FA code, it'll call that URL to grab the code and automate whatever is behind that paywall! Want to learn more? Read our advanced feature documentation here: https://lnkd.in/gmKkdJ55

10

3件のコメント

Ethernet always wins. It has already adopted most of the features of Infiniband. Now, Meta reports Ethernet is more reliable.

14

Building a Real-Time GenAI-Powered Food Delivery App with Redpanda Data Thanks Christina Lin https://lnkd.in/gHNfC-eA Harnessing the Power of Real-Time Data and Generative AI for Superior Delivery Experiences The food delivery industry is undergoing a rapid transformation, driven by the increasing demand for speed, convenience, and personalization. To meet these evolving customer expectations, businesses must leverage cutting-edge technologies like Generative AI (#GenAI) and real-time data processing platforms. Key Components of a Redpanda-Powered GenAI Food Delivery App: Real-Time Data Ingestion: Capture a continuous stream of data from various sources, including order placement, restaurant updates, delivery agent locations, and customer feedback. Data Enrichment and Transformation: Utilize Redpanda's in-situ data processing capabilities with WebAssembly (WASM) to clean, transform, and enrich data on the fly. GenAI Model Integration: Integrate advanced language models into the Redpanda pipeline to generate dynamic content, such as personalized recommendations, order summaries, and customer support interactions. Real-Time Predictions: Leverage AI to predict delivery times, optimize routes, and anticipate demand fluctuations. Continuous Learning: Continuously train and refine AI models using real-time data feedback to improve accuracy and performance. Benefits of a Redpanda-Powered GenAI Food Delivery App: Enhanced Customer Experience: Deliver personalized recommendations, real-time order tracking, and proactive customer support. Optimized Operations: Improve delivery efficiency, reduce costs, and increase driver satisfaction through intelligent routing and resource allocation. Competitive Advantage: Gain a first-mover advantage by offering innovative features and superior service. Data-Driven Decision Making: Make informed business decisions based on real-time insights and analytics. General Hashtags #Redpanda #GenAI #ArtificialIntelligence #MachineLearning #DataScience #RealTimeData #FoodDelivery #Tech #Innovation #Technology #DataDriven #DigitalTransformation More Specific Hashtags #RedpandaPoweredAI #RealTimeDelivery #AIforFoodDelivery #FoodTech #DeliveryOptimization #CustomerExperience #DataEngineering #WASM #TensorFlow #AIandBusiness Engaging Hashtags #FutureofFoodDelivery #TechTrends #Disruptor #InnovationThatMatters #TechForGood #SmartDelivery

9

Thanks to Youngjin Kim and Moweon Lee, two experienced Naver engineers with years of expertise in big data analytics, for sharing how they use StarRocks in complex real-time data analytics scenarios. Youngjin highlighted the reasons why Naver chose StarRocks: • 🚀Strong JOIN Performance • 🚀Smart Cache Strategy • 🚀Cloud Native Storage • 🚀Analytics with Flexibility • 🚀Materialized View To learn more, check out this impressive video: https://lnkd.in/gHu-WZND

7

Flux - 2024 DALL-e 3 - 2023 ChatGPT - 2022 Midjourney - 2022 DALL-e 2 - 2022 Stable Diffusion - 2022 DALL-e 1 - 2021 𝗡𝗶𝗴𝗵𝘁𝗖𝗮𝗳𝗲 - 𝟮𝟬𝟭𝟵 When I started NightCafe in 2019, "generative AI" wasn't even really a term - certainly not a ubiquitous one. I started NightCafe as a side-project, using an old algorithm called "Neural Style Transfer" to let people make personalised art to put up on their walls. I never expected it to be more than a side-project, and for the first few years it was a money pit - people enjoyed creating the images, but no-one really wanted to buy a print (which was the business model at the time). But then in 2021 after the announcement of DALL-e 1 (which was never actually released), things started happening in the newly-coined "generative art" space. Being in the right place at the right time, NightCafe was actually the first website where you could create images from a text prompt (without looking at any Python code). Things have moved quickly since then. In 2022, NightCafe contributed to the training costs of what would become "Stable Diffusion" while Stability AI was still in stealth mode. When Stable Diffusion was released, things got even crazier. We went from having maybe 10 competitors (mostly not serious ones) to 100 then 1000 then 10,000 in a matter of a few months. While VCs were funding many of these, and reaching out to us for intro calls, we've remained bootstrapped this whole time. This month is our 5th birthday, and we're also celebrating 1 Billion images generated on NightCafe. We've grown to a team of 10, have over 20,000 active paying users and what I think is the most positive and active community of AI art enthusiasts in the world. Happy Birthday to us :) And thanks so much to the team that has accomplished all this - Elle Russell, Samuel Sargent, Cassandra Hood, Max Puckeridge, Jon Alonso, Shamim Jahandideh, Matt Treacey, Ivana, Jemima

65

13件のコメント

From YC W24

30

4件のコメント

A software engineer I interviewed yesterday just changed everything... Let me explain: Yesterday, I was on an interview with Frank R.. A software engineer we were talking to for the new Full-Stack Engineer role started telling us about how much he loves the platform. He told us he was turn his favorite song lyrics into the short-form videos on the ossa.ai platform, and then sending them to his wife. Right away, my founder cap was put on, and we started asking questions about what he liked and what he thought could be better. One thing he mentioned was that the landing page could be more clear about what the product does. He was right. Our headline on the landing page was currently "The #1 AI-Tool for Short-Form Content Creators." That headline doesn't tell a new visitor what the product does. Right after the call, I created a ticket in the engineering backlog for our Head of Growth, Brennan Duncan, to change the headline to "Text to Short-Form Video In Minutes." Since that conversation yesterday morning, we have seen a significant jump in conversion rates. Moral of the story? Always be learning and listening to your users. P.S. - We just dropped a massive new feature that no other company in the world has thought about trying to create. You can check it out below. ⤵ https://lnkd.in/gZh_bPpM

20

7件のコメント

Jensen Huang is at the center of the Universe rn, and #AI is the Force that's driving the Universe. That's the message I got at the recently concluded #GartnerSymposium. Every major / minor tech vendor was present and everyone had AI offerings, from #RPA to #AgenticPlatforms. It has been this way for the past 18 months at every major conference I attended, the pitch becoming more & more intensive and new buzzwords coming to life by day. Is this just another fad like several we had seen in the past? Or will AI fundamentally alter the way we live, work and interact with the world? I do believe AI is as transformational to the world as Steam engine, Electricity and Transistor that had profound impact on the humanity. But, the hype also makes it incredibly hard to fathom it and develop action plans. - Where do organizations start with AI investmens? - How do CEOs and CIOs strategically prioritize the investments? - Should one go big bang with Agentic Platforms from mega vendors and provide AI access to all employees? - Or start with small pilots in individual departments? - How does one ensure their data is secure, its not used for training AI models and hence lose competitive advantage? - What guardrails are necessary to ensure governance? - How much should one worry about hallucinations? - How does one keep cost in check (cloud vendor AI costs are hard to estimate and can quickly go out of control)? What are your thoughts, fears and insights? Please lmk in comments. #AI #GenAI #LLM ##AgenticPlatforms #Governance

38

1件のコメント

Hi All, For those who are not fully familiar with woc.space, I'd like to share our roadmap for the upcoming period (June - July 2024). 1. List Mode: Introducing a new list view for better file management. 2. Server-Side Compression Download: Enable faster downloads with server-side file compression. 3. Overseas OSS Migration to Vol Engine: Transitioning our overseas Object Storage Service to the Vol engine for improved performance. 4. Folder Support: Adding support for managing and organizing files in folders. 5. File Restore: Implementing a feature to restore deleted files. Move/Copy Files: Allow users to move or copy files easily within the platform. 6. Preview Feature Enhancement: Improving the file preview functionality. General Bug Fixes: Addressing various bugs to enhance stability and performance. 7. Search & Tag: Introducing advanced search and tagging capabilities. 8. AI Features per File Format: Adding AI-driven functionalities tailored to specific file formats. 9. Global Transfer Improvement: Enhancing global file transfer speeds and reliability. We look forward to bringing these exciting updates to you soon!

3

A French startup Kyutai has just dropped their rival to gpt4o - a 7B model named Moshi. They have plans to take it open sourse. - Exceptional vocal capabilities for smooth, natural, and expressive text-to-speech communication. Seems to articulate quite well- you can try it out (link below) - Demonstrates creativity and versatility, serving as a coach or companion with immersive interactions. - Freely available online for public testing. - Can operate offline, unlike GPT-4. - Faster response time (200 ms) compared to GPT-4o. Its so fast it even interrupted the speaker sometimes😁 - Capable of various accents and 70 emotional styles. - Can listen and talk simultaneously. This has to be ironed out a little i think. - Compact design ensures secure use on disconnected devices. - Plans to release code and model weights with open source license. - Future enhancements include audio identification, watermarking, and signature tracking. Try it: https://lnkd.in/g5dqh5ZE Video demo link: https://lnkd.in/g9gbfRRb Source: https://lnkd.in/gJu5KaWa

2

Today we're (Kritin Vongthongsri) launching DeepEval v1.0.0 ⭐, a production-grade open-source LLM evaluation framework (https://lnkd.in/gmFaWYh7). Over the past year, DeepEval has been used by LLM engineers and data scientist around the world and ran over 2m LLM evaluations, with use cases including RAG pipeline evaluation, benchmarking LLMs on popular research benchmarks like MMLU; and for our final feature for v1.0.0, we're extending support to evaluate LLM Agents and LLM conversations. Here are reasons why you might consider using DeepEval for LLM system QA: - Regression & unit test LLM systems in ANY CI/CD environment, and integrated with Pytest. - 14+ research backed LLM evaluation metrics, now including metrics for LLM Agents and LLM Chatbots, covering literally ALL use cases and evaluation criteria. - Use literally any LLM for evaluation, including those users working in air gapped environments. - SOTA synthetic data generation for multiple different use cases, may it be QA, Text-SQL, for red-teaming LLMs, etc., which you can again use any LLM for. - Supports logging evaluation cost, caching evaluation results, running evaluations in parallel, evaluation error handling, token usage, saving results to local files, and fully integrated with @Confident AI for real-time evaluations. - Integration with Hugging Face transformers and LlamaIndex for users that are fine-tuning, building open-source models, or those building LLM systems. - Seven research benchmarks we made publicly available, including MMLU, BBH, HellaSwag, etc. Now you can benchmark literally any LLM using these popular benchmarks in 3 lines of code, with detailed task score breakdowns, in any environment setup. Lastly, users have the ability to create custom metrics easily in code, and automatically get fully integrated with ALL the features mentioned above^🙂 Version v2.0.0 is already in progress, with an emphasis on democratizing LLM red-teaming, LLM security, responsible AI, and multi-modal LLM evaluation. Support us by giving us a star on GitHub ⭐! It will help more people discover what we're doing. Github link here: https://lnkd.in/gmFaWYh7 #machinelearning #llms #llmops #opensource #generativeai #llmevaluation #rag. #datascience

46