We are seeking experienced Python developers for the Zapia AI team, with expertise in designing and implementing asynchronous, cloud-based distributed systems. Ideal candidates will have a strong background in scalability, concurrency, and system monitoring. Proficiency in PostgreSQL, Redis, Google Cloud Platform (GCP), FastAPI, Flask, Docker, and ElasticSearch is highly desired. Apply here: https://lnkd.in/dp6Jq2NR
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👋 Devs: Learn how to use LangChain and Milvus to build search engines for use cases ranging from a simple document search to applications in eCommerce, image, and video search! Check out this starter guide from Ayush Pandey, Senior Software Engineer at Intuit: https://bit.ly/3RsLArT #Milvus #LangChain #AI
Building AI-powered search using LangChain and Milvus
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Our top 3 AI picks of the day are: 1/ Mistral AI has raised $415M in its series A. We covered the leaks of Mistral’s Series A at $2B valuation on Friday and in the few days that went by they have launched an open-weights LLM that smokes GPT 3.5, their dev platform and API. a16z wrote about why they are investing in Mistral: https://lnkd.in/dqJGr9qe 2/ Atlassian has released the first set of AI capabilities across its products like Jira, Confluence, and Bitbucket under the name Atlassian Intelligence. Atlassian Intelligence is available to customers with features like summaries, natural language to JQL, virtual agents and more coming soon. Our detailed summary: https://lnkd.in/dMMQbaRQ 3/ General World Models by Runway ML - Runway is announcing a new research effort to create world models that build an internal representation of an environment and use it to simulate future events within that environment. #AI #Mistral #RunwayML
Investing in Mistral | Andreessen Horowitz
https://a16z.com
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Ray is an #opensource project that makes it simple to scale any compute-intensive #Python workload. Industry leaders like Uber, Shopify, and Spotify are building their next-generation ML platforms on top of Ray. Zhe Zhang introduces the basic API & architectural concepts of Ray, and dives deeper into some of its innovative ML use cases: https://bit.ly/3LPtdM0 #InfoQ #AI #ML
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META recently made a massive investment to train large language models at scale - they now have shared a great overview of their learnings and challenges. Some of the key innovations that enabled META to succeed (so far) have included optimizing GPU connectivity, leveraging advanced scheduling algorithms, and adapting high-performance hardware. Meta has implemented robust network infrastructures that showcase the nuance required to support massive GPU clusters - this is an endevour that will only grow more ubiquitously across tech companies fighting across the AI race. Blog post: https://lnkd.in/gibEeTdp -- If you liked this article you can join 60,000 practitioners for weekly tutorials, resources, OSS frameworks, and MLOps events across the machine learning ecosystem: https://lnkd.in/eRBQzVcA #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps #augmentedintelligence #deeplearning #privacy #kubernetes #datascience #python #bigdata
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META recently made a massive investment to train large language models at scale - they now have shared a great overview of their learnings and challenges. Some of the key innovations that enabled META to succeed (so far) have included optimizing GPU connectivity, leveraging advanced scheduling algorithms, and adapting high-performance hardware. Meta has implemented robust network infrastructures that showcase the nuance required to support massive GPU clusters - this is an endevour that will only grow more ubiquitously across tech companies fighting across the AI race. Blog post: https://lnkd.in/ecAW7GUb -- If you liked this article you can join 60,000 practitioners for weekly tutorials, resources, OSS frameworks, and MLOps events across the machine learning ecosystem: https://lnkd.in/eRBQzVcA #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps #augmentedintelligence #deeplearning #privacy #kubernetes #datascience #python #bigdata
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Open Source AI is Changing the Game! 🚀 Open-source AI is taking the tech world by storm, driving incredible advancements thanks to platforms like GitHub and Hugging Face. Unlike big tech companies, open-source projects are faster, more adaptable, and often more efficient. Key Highlights: - Open-source models like Mistral and Llama are catching up with top closed-source models. - GitHub saw a 148% increase in contributions to AI projects last year. - Python remains the top language for AI, with Mojo emerging as a new favorite for its performance. Open-source AI is thriving and reshaping the future of technology. Want to dive deeper? Check out this detailed article : https://shorturl.at/EbrFU #AI #OpenSource #Innovation #Tech
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Growing misuse and misapplication of Gen AI is disrupting its adoption by many organizations, citing privacy and security concerns. To mitigate Gen AI exploitation, companies need to develop capabilities to detect, identify, and prevent the spread of such mishandling. Get more on the latest findings by Harward Business Review here: https://lnkd.in/g3UHim_w #computerscience #python #fintech #ai #bigdata #softwareengineering #programing #analytics #softwaredesign #datamining #data #cloud #automation #userexperience #cloudcomputing #mobileapplications #deeplearning #datascience #research #fintech
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Are you curious about the future of the tech industry in the midst of the rapid advancements of AI? 🤖 The rapid development of artificial intelligence has caused significant worry to different fields, one of which is the very industry that birthed it: the tech industry 👨💻. These breakthroughs, along with the overwhelming news of tech layoffs bring about a great deal of uncertainties for both beginners and professionals alike. But the integration of AI to the industry isn't all that bad! Learn more as we dive more into this topic in our article! ✨ Thanks to Angela Kim R. Masong and Guy Ivan Ocon for their contributions! #SPARCS #aiadoption #techcareers #techcommunity #artificialintelligence
The AI Tech Revolution: Will AI be replacing programmers?
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Considering its implacable attitude of gatekeeping and elitism, (in my opinion) AI is hardly the scapegoat in Stackoverflow's decline. Contrariwise, "the AI boom" could have increased traffic with all the new questions about the frameworks (Tensorflow, PyTorch, Jax, etc.) or foundation model fine-tuning. It was my go-to site, and I remember downloading its entire dataset when some high-profile websites got banned in my country. However, it failed to prevent the destruction caused by some of its power-tripping moderators. With time, it became a platform where - One can't ask some basic questions without getting slapped with a "duplicate" label - One can't get answers for the niche questions that would not result in an easy karma farming - If you are using a newer version of a library, good luck finding a working solution that does not require some depreciated method of the previous versions. Yesteryear, I realized that, more often than not, my search queries included "site:reddit.com". So, in my case, history became legend; legend is becoming myth. #programming #ai #stackoverflow https://lnkd.in/dR_kbSBX
Stack Overflow lays off over 100 people as the AI coding boom continues
theverge.com
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