Machine Learning Tech Brief By HackerNoon

Machine Learning Tech Brief By HackerNoon

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Machine Learning Tech Brief By HackerNoon episodes

  • Error 404! Problems Organizations Need To Avoid When Implementing Artificial Intelligence

    This story was originally published on HackerNoon at: https://hackernoon.com/error-404-problems-organizations-need-to-avoid-when-implementing-artificial-intelligence.


    While artificial intelligence has been enjoying its moment in the sun, quite literally, the year ahead only brings more opportunities and new challenges.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #ai-implementation-tips, #ai-implementation-strategies, #how-to-implement-ai-at-work, #using-ai-for-your-business, #ai-adoption-survey, #ai-risk-management-strategy, #ai-implementation-budget, #hackernoon-top-story, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.


    This story was written by: @jwolinsky. Learn more about this writer by checking @jwolinsky's about page,
    and for more stories, please visit hackernoon.com.


    While artificial intelligence has been enjoying its moment in the sun, quite literally, the year ahead only brings more opportunities and new challenges.

    14 min
  • Studio Neiro: A New Platform for Video Marketing

    This story was originally published on HackerNoon at: https://hackernoon.com/studio-neiro-a-new-platform-for-video-marketing.


    Connect and Captivate with AI Avatars. Create personalized and engaging videos with AI avatars at scale. Leverage the power of Neiro for your business
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #ai-applications, #video-editing-apps, #ai-generative, #digital-marketing, #digital-contents, #studio-neiro, #press-release, #good-company, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.


    This story was written by: @studioneiroai. Learn more about this writer by checking @studioneiroai's about page,
    and for more stories, please visit hackernoon.com.


    Studio Neiro heralds a pioneering platform, seamlessly translating text into captivating videos with minimal coding effort. The platform eradicates the need for extravagant influencer marketing campaigns, offering an extensive array of pre-designed avatars. With a vast selection of 70 voices, users can meticulously choose the ideal voice for their project and even adjust emotional nuances.

    4 min
  • Humans vs. Machines: When AI Goes Rogue

    This story was originally published on HackerNoon at: https://hackernoon.com/humans-vs-machines-when-ai-goes-rogue.


    AI’s role in decision-making and automation is rapidly expanding. There is, however, an underlying tension to our technological prowess.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #rogue-ai, #rogue-artifical-intelligence, #humans-vs-machines, #llms-can-deceive-users, #does-an-ai-lie, #strategic-deception-in-ai, #role-of-environmental-factors, #ai-model-variance, and more.


    This story was written by: @adrien-book. Learn more about this writer by checking @adrien-book's about page,
    and for more stories, please visit hackernoon.com.


    AI’s role in decision-making and automation is rapidly expanding. There is, however, an underlying tension to our technological prowess

    6 min
  • Into the Future: 24 Tech Predictions Shaping 2024

    This story was originally published on HackerNoon at: https://hackernoon.com/into-the-future-24-tech-predictions-shaping-2024.


    From Green AI to War Tech and Memeland, it’s going to be a bumpy ride.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #ai, #future, #tech, #technology, #predictions, #social-media, #artificial-intelligence, #crypto, and more.


    This story was written by: @adrien-book. Learn more about this writer by checking @adrien-book's about page,
    and for more stories, please visit hackernoon.com.


    From Green AI to War Tech and Memeland, 2024 is going to be a wild year for tech.

    27 min
  • AI is Helping Clean Our Oceans of Plastics

    This story was originally published on HackerNoon at: https://hackernoon.com/ai-is-helping-clean-our-oceans-of-plastics.


    AI technologies, particularly in the form of machine learning and data analytics, are being employed to identify, track, and ultimately remove microplastics.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #ai-applications, #ocean-pollution, #plastic-pollution, #the-ocean-cleanup, #ai-for-pollution, #ai-is-helping-clean-our-oceans, #ocean-cleaning-tech, #ocean-cleanup-efforts, and more.


    This story was written by: @allan-grain. Learn more about this writer by checking @allan-grain's about page,
    and for more stories, please visit hackernoon.com.


    Microplastics, tiny plastic fragments less than five millimeters in size, pose a significant threat to marine life and ecosystems. Startups are at the forefront of integrating AI into ocean cleanup efforts. The role of AI in fighting microplastics in our oceans is multifaceted, encompassing detection, cleanup, prevention, and public engagement.

    5 min
  • How to Effectively Evaluate Your RAG + LLM Applications

    This story was originally published on HackerNoon at: https://hackernoon.com/how-to-effectively-evaluate-your-rag-llm-applications.


    Ever wondered how some of today's applications seem almost magically smart? A big part of that magic comes from something called RAG and LLM.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #rag-architecture, #rag-plus-llm-applications, #dual-role-of-master-llm, #llm-cycle-of-improvement, #human-in-loop-feedback, #prompt-tuning-by-master-llm, #automating-evaluation-pipeline, #hackernoon-top-story, and more.


    This story was written by: @vndee. Learn more about this writer by checking @vndee's about page,
    and for more stories, please visit hackernoon.com.


    Ever wondered how some of today's applications seem almost magically smart? A big part of that magic comes from something called RAG and LLM.

    14 min
  • So, How Do They Really Train AI Models?

    This story was originally published on HackerNoon at: https://hackernoon.com/so-how-do-they-really-train-ai-models.


    Generative AI models are a fascinating technology that humans still are not able to fully harness.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #ai-training-models, #what-is-supervised-learning, #what-is-unsupervised-learning, #what-is-reinforcement-learning, #learning-from-interaction, #obtain-data-for-ai-models, #where-does-ai-data-come-from, #stability-ai-case, and more.


    This story was written by: @mayankvikash. Learn more about this writer by checking @mayankvikash's about page,
    and for more stories, please visit hackernoon.com.


    Generative AI models are a fascinating technology that humans still are not able to fully harness.

    7 min
  • How to Use an Uncensored AI Model and Train It With Your Data

    This story was originally published on HackerNoon at: https://hackernoon.com/how-to-use-an-uncensored-ai-model-and-train-it-with-your-data.


    Learn how to run Mixtral locally and have your own AI-powered terminal, remove its censorship, and train it with the data you want.
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #ai, #chatgpt, #llms, #ai-trends, #future-of-ai, #futurism, #hackernoon-top-story, #mistral, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.


    This story was written by: @jeferson. Learn more about this writer by checking @jeferson's about page,
    and for more stories, please visit hackernoon.com.


    Mistral is a French startup, created by former Meta and DeepMind researchers. Under the Apache 2.0 license, this model claims to be more powerful than LLaMA 2 and ChatGPT 3.5, all that while being completely open-source. We are going to learn how to use it uncensored and discover how to train it with our data.

    4 min
  • Gemini - A Family of Highly Capable Multimodal Models: Evaluation

    This story was originally published on HackerNoon at: https://hackernoon.com/gemini-a-family-of-highly-capable-multimodal-models-evaluation.


    Gemini - A Family of Highly Capable Multimodal Models: Evaluation
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #generative-ai, #machine-learning, #gemini-model-evaluation, #gemini-family-of-models, #google-gemini, #multimodal-llm, #gemini-pro-vs-gemini-ultra, #gemini-modality-combination, and more.


    This story was written by: @escholar. Learn more about this writer by checking @escholar's about page,
    and for more stories, please visit hackernoon.com.


    This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks — notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of Gemini models in cross-modal reasoning and language understanding will enable a wide variety of use cases and we discuss our approach toward deploying them responsibly to users.

    26 min
  • Gemini - A Family of Highly Capable Multimodal Models: Discussion and Conclusion, References

    This story was originally published on HackerNoon at: https://hackernoon.com/gemini-a-family-of-highly-capable-multimodal-models-discussion-and-conclusion-references.


    Gemini - A Family of Highly Capable Multimodal Models: Discussion and Conclusion, References
    Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
    You can also check exclusive content about #generative-ai, #future-of-ai, #multimodal-models, #multimodal-gemini-models, #hackernoon-scholar, #google-gemini, #gemini-model-family, #multimodal-ml-models, and more.


    This story was written by: @escholar. Learn more about this writer by checking @escholar's about page,
    and for more stories, please visit hackernoon.com.


    This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks — notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of Gemini models in cross-modal reasoning and language understanding will enable a wide variety of use cases and we discuss our approach toward deploying them responsibly to users.

    1 hr

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