Europe Says<p><a href="https://www.europesays.com/2137381/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">europesays.com/2137381/</span><span class="invisible"></span></a> Can Cold Exposure Alter Energy Dynamics in Obesity? <a href="https://pubeurope.com/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://pubeurope.com/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://pubeurope.com/tags/ArtificialNeuralNetworks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ArtificialNeuralNetworks</span></a> <a href="https://pubeurope.com/tags/blood" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>blood</span></a> <a href="https://pubeurope.com/tags/Canada" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Canada</span></a>;Canadian <a href="https://pubeurope.com/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://pubeurope.com/tags/Energy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Energy</span></a> <a href="https://pubeurope.com/tags/exercise" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>exercise</span></a> <a href="https://pubeurope.com/tags/Grant" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Grant</span></a> <a href="https://pubeurope.com/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://pubeurope.com/tags/MLNaturalLanguageProcessing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLNaturalLanguageProcessing</span></a> <a href="https://pubeurope.com/tags/NPL" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NPL</span></a> <a href="https://pubeurope.com/tags/obese" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>obese</span></a> <a href="https://pubeurope.com/tags/obesity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>obesity</span></a> <a href="https://pubeurope.com/tags/PhysicalActivity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PhysicalActivity</span></a> <a href="https://pubeurope.com/tags/WeightLoss" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WeightLoss</span></a> <a href="https://pubeurope.com/tags/WeightManagement" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WeightManagement</span></a></p>
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#deeplearning
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ma𝕏pool<p>Deep learning gets the glory, deep fact checking gets ignored. When impressive AI biology results are full of errors</p><p><a href="https://rachel.fast.ai/posts/2025-06-04-enzyme-ml-fails/index.html" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">rachel.fast.ai/posts/2025-06-0</span><span class="invisible">4-enzyme-ml-fails/index.html</span></a></p><p><a href="https://mathstodon.xyz/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a> <a href="https://mathstodon.xyz/tags/biochemistry" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>biochemistry</span></a> <a href="https://mathstodon.xyz/tags/computationalChemistry" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>computationalChemistry</span></a> <a href="https://mathstodon.xyz/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a></p>
Hacker News<p>Deep learning gets the glory, deep fact checking gets ignored</p><p><a href="https://rachel.fast.ai/posts/2025-06-04-enzyme-ml-fails/index.html" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">rachel.fast.ai/posts/2025-06-0</span><span class="invisible">4-enzyme-ml-fails/index.html</span></a></p><p><a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>HackerNews</span></a> <a href="https://mastodon.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> <a href="https://mastodon.social/tags/factchecking" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>factchecking</span></a> <a href="https://mastodon.social/tags/ML" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ML</span></a> <a href="https://mastodon.social/tags/ethics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ethics</span></a> <a href="https://mastodon.social/tags/AIresearch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AIresearch</span></a></p>
PKPs Powerfromspace1<p>Hmmmm 🤔 💭 </p><p><a href="https://mstdn.social/tags/artificialintelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>artificialintelligence</span></a> <a href="https://mstdn.social/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a> <a href="https://mstdn.social/tags/machinelearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machinelearning</span></a> <a href="https://mstdn.social/tags/aiart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>aiart</span></a> <a href="https://mstdn.social/tags/digitalart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>digitalart</span></a> <a href="https://mstdn.social/tags/technology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>technology</span></a> <a href="https://mstdn.social/tags/art" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>art</span></a> <a href="https://mstdn.social/tags/aiartcommunity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>aiartcommunity</span></a> <a href="https://mstdn.social/tags/midjourney" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>midjourney</span></a> <a href="https://mstdn.social/tags/datascience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>datascience</span></a> <a href="https://mstdn.social/tags/generativeart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>generativeart</span></a> <a href="https://mstdn.social/tags/innovation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>innovation</span></a> <a href="https://mstdn.social/tags/tech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tech</span></a> <a href="https://mstdn.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> <a href="https://mstdn.social/tags/python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>python</span></a> <a href="https://mstdn.social/tags/midjourneyart" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>midjourneyart</span></a> <a href="https://mstdn.social/tags/aiartwork" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>aiartwork</span></a> <a href="https://mstdn.social/tags/aiartist" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>aiartist</span></a> <a href="https://mstdn.social/tags/programming" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>programming</span></a> <a href="https://mstdn.social/tags/robotics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>robotics</span></a> <a href="https://mstdn.social/tags/bigdata" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bigdata</span></a> <a href="https://mstdn.social/tags/artoftheday" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>artoftheday</span></a> <a href="https://mstdn.social/tags/coding" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>coding</span></a> <a href="https://mstdn.social/tags/aiartists" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>aiartists</span></a> <a href="https://mstdn.social/tags/SkyNet" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SkyNet</span></a> is Us </p><p><a href="https://bsky.app/profile/sterlingworldrecs.bsky.social/post/3lpyv5niu322s" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">bsky.app/profile/sterlingworld</span><span class="invisible">recs.bsky.social/post/3lpyv5niu322s</span></a></p>
Europe Says<p><a href="https://www.europesays.com/2113345/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">europesays.com/2113345/</span><span class="invisible"></span></a> New MVTec HALCON Version Includes Deep Learning-Based Technology <a href="https://pubeurope.com/tags/america" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>america</span></a> <a href="https://pubeurope.com/tags/ArtificialIntelligenceAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ArtificialIntelligenceAI</span></a> <a href="https://pubeurope.com/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a>(DL) <a href="https://pubeurope.com/tags/MachineVision" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineVision</span></a> <a href="https://pubeurope.com/tags/manufacturing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>manufacturing</span></a> <a href="https://pubeurope.com/tags/metrology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>metrology</span></a> <a href="https://pubeurope.com/tags/science" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>science</span></a> <a href="https://pubeurope.com/tags/technology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>technology</span></a> <a href="https://pubeurope.com/tags/UnitedStates" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UnitedStates</span></a> <a href="https://pubeurope.com/tags/UnitedStatesOfAmerica" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UnitedStatesOfAmerica</span></a> <a href="https://pubeurope.com/tags/US" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>US</span></a> <a href="https://pubeurope.com/tags/USA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>USA</span></a></p>
Svenja Guhr<p>Based on an analysis of <a href="https://fedihum.org/tags/DHd" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DHd</span></a> conference abstracts, I trace the evolution of <a href="https://fedihum.org/tags/CLS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CLS</span></a> methods from 2014 to 2025: from omnipresent <a href="https://fedihum.org/tags/NetworkAnalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NetworkAnalysis</span></a> and <a href="https://fedihum.org/tags/Annotation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Annotation</span></a>, to the first appearance of <a href="https://fedihum.org/tags/TopicModeling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>TopicModeling</span></a> and <a href="https://fedihum.org/tags/SentimentAnalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SentimentAnalysis</span></a>, to <a href="https://fedihum.org/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> and <a href="https://fedihum.org/tags/GenerativeAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GenerativeAI</span></a>.</p>
UK<p><a href="https://www.europesays.com/uk/90701/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">europesays.com/uk/90701/</span><span class="invisible"></span></a> AI Tool Reads Faces to Predict Health, Aging, and Cancer Outcomes <a href="https://pubeurope.com/tags/Aging" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Aging</span></a> <a href="https://pubeurope.com/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://pubeurope.com/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://pubeurope.com/tags/BrainCancer" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BrainCancer</span></a> <a href="https://pubeurope.com/tags/BrainResearch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BrainResearch</span></a> <a href="https://pubeurope.com/tags/Cancer" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Cancer</span></a> <a href="https://pubeurope.com/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://pubeurope.com/tags/Health" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Health</span></a> <a href="https://pubeurope.com/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://pubeurope.com/tags/MassGeneral" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MassGeneral</span></a> <a href="https://pubeurope.com/tags/neurobiology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>neurobiology</span></a> <a href="https://pubeurope.com/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Neuroscience</span></a> <a href="https://pubeurope.com/tags/Technology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Technology</span></a> <a href="https://pubeurope.com/tags/UK" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UK</span></a> <a href="https://pubeurope.com/tags/UnitedKingdom" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UnitedKingdom</span></a></p>
David Patton<p>Join me in-person or online as we apply lessons learned about AgenticRAG tomorrow evening. We have 3 presentations planned showing some custom agents we have coded. <a href="https://dmv.community/tags/AgenticAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AgenticAI</span></a>, <a href="https://dmv.community/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://dmv.community/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://dmv.community/tags/AgenticRAG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AgenticRAG</span></a> <a href="https://dmv.community/tags/LlamaIndex" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LlamaIndex</span></a></p><p><a href="https://www.meetup.com/deep-learning-adventures/events/306500825/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">meetup.com/deep-learning-adven</span><span class="invisible">tures/events/306500825/</span></a></p>
Leanpub<p>The Hundred-Page Language Models Book by Andriy Burkov is on sale on Leanpub! Its suggested price is $50.00; get it for $20.00 with this coupon: <a href="https://leanpub.com/sh/3u98EIgF" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">leanpub.com/sh/3u98EIgF</span><span class="invisible"></span></a> <a href="https://mastodon.social/tags/Ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Ai</span></a> <a href="https://mastodon.social/tags/Gpt" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Gpt</span></a> <a href="https://mastodon.social/tags/NeuralNetworks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NeuralNetworks</span></a> <a href="https://mastodon.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.social/tags/ComputerScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ComputerScience</span></a> <a href="https://mastodon.social/tags/Linguistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Linguistics</span></a></p>
Petr Nuska<p>However, neither this method had a satisfactory data output that would suit the <a href="https://mastodon.world/tags/RomChords" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RomChords</span></a> project’s purposes. Even the state-of-the-art polyphonic detection algorithms (such as the one developed by Celemony Melodyne) produce a lot of noise, and cleaning the data to a standard usable for the project would be enormously laborious.</p><p>(Although it is possible that in a few years, progress in <a href="https://mastodon.world/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> will make this method much more effective and efficient).</p><p><a href="https://mastodon.world/tags/RomaniChords" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RomaniChords</span></a></p><p>🧵7/20</p>
Jody Hughes<p>I was wondering what the energy cost is for taking advantage of the translate button that appears on toots in other languages. (Is this app-specific?) </p><p>It tells me it uses DeepLearning, which touts itself as using AI, but I doubt it has the energy cost of the big LLMs. Does anybody know?</p><p><a href="https://cupoftea.social/tags/Translation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Translation</span></a> <a href="https://cupoftea.social/tags/Mastodon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mastodon</span></a> <a href="https://cupoftea.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a></p>
Ruth Mottram<p>My (and <span class="h-card" translate="no"><a href="https://mastodon.world/@AarhusUni" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>AarhusUni</span></a></span> ) PhD student Elke Schlager is presenting some of her work on <a href="https://fediscience.org/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> applications over the <a href="https://fediscience.org/tags/Greenland" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Greenland</span></a> ice sheet. Very cool, very exciting work.</p>
Debby<p>DeepSeek-V3: A New Era in Open-Source AI with a Comedic Twist</p><p>In the ever-evolving landscape of artificial intelligence, public and open models are once again catching up with their proprietary counterparts. The recent launch of DeepSeek-V3 has stirred excitement by outperforming even Sonnet and ChatGPT in certain benchmarks. This open-source model, developed by Hangzhou DeepSeek Artificial Intelligence and Beijing DeepSeek Artificial Intelligence, boasts an impressive 671 billion parameters, making it the largest model in the open-source community. With its advanced Mixture-of-Experts (MoE) architecture and innovative technologies, DeepSeek-V3 not only outperforms its open-source counterparts like LLaMA but also rivals closed models such as Sonnet 3.5 and ChatGPT-4o.<br>The Power of Open Source</p><p>One of the most remarkable aspects of DeepSeek-V3 is its commitment to accessibility. By being open-source, it allows researchers and developers from around the globe to experiment, innovate, and contribute to the AI community. While it does require around 400GB of RAM to run locally, that likely won’t deter anyone from deploying it on their server. The model's documentation and training frameworks are readily available on platforms like Hugging Face, fostering collaboration and knowledge sharing. This democratization of AI technology is a significant step forward, enabling a diverse range of applications from education to programming.<br>Technical Innovations</p><p>DeepSeek-V3 is not just about size; it’s about performance. With a processing speed of 60 tokens per second—three times faster than its predecessor—this model is designed for efficiency. The incorporation of FP8 mixed precision training reduces GPU memory consumption without sacrificing accuracy, while the DualPipe algorithm enhances processing efficiency. These advancements not only improve performance but also keep training costs competitive, making DeepSeek-V3 a viable option for various applications.<br>A Comedic Twist: The Identity Crisis</p><p>However, the launch of DeepSeek-V3 has not been without its quirks. In a rather amusing turn of events, the model seems to have developed an identity crisis, often identifying itself as ChatGPT during interactions. This phenomenon has sparked laughter and intrigue within the tech community. As reported by TechCrunch, DeepSeek-V3 claimed to be a version of OpenAI’s GPT-4 model in five out of eight generations during tests. This raises questions about the model's training data and the potential for "hallucinations"—a term used to describe AI's tendency to generate inaccurate or misleading information.</p><p>While some may find this amusing, it highlights a critical issue in the AI field: the challenge of ensuring the integrity and accuracy of training data. As AI models increasingly draw from a web saturated with AI-generated content, the risk of misidentification and misinformation grows. This situation serves as a reminder of the importance of transparency and ethical practices in AI development.<br>Looking Ahead</p><p>Despite its comedic missteps, DeepSeek-V3 stands as a testament to the potential of open-source AI. Its impressive performance metrics and commitment to accessibility position it as a benchmark in the industry. As the DeepSeek team continues to innovate—introducing features like “Deep Roles” for customizable AI interactions—the future looks bright for this model.</p><p>In conclusion, DeepSeek-V3 not only represents a significant leap forward in open-source AI technology but also provides a lighthearted reminder of the complexities and quirks inherent in artificial intelligence. As we navigate this exciting frontier, let’s embrace both the advancements and the occasional hilarity that comes with it. Whether you’re a developer looking to explore new possibilities or simply someone who enjoys a good laugh at AI’s expense, DeepSeek-V3 is worth keeping an eye on.</p><p>Try it out here: DeepSeek-V3 <a href="https://chat.deepseek.com/sign_in" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">chat.deepseek.com/sign_in</span><span class="invisible"></span></a></p><p>Explore more on Hugging Face: Hugging Face - DeepSeek-V3 <a href="https://huggingface.co/deepseek-ai/DeepSeek-V3" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">huggingface.co/deepseek-ai/Dee</span><span class="invisible">pSeek-V3</span></a></p><p><a href="https://hear-me.social/tags/DeepSeekV3" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepSeekV3</span></a> <a href="https://hear-me.social/tags/OpenSourceAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenSourceAI</span></a> <a href="https://hear-me.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://hear-me.social/tags/AIInnovation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AIInnovation</span></a> <a href="https://hear-me.social/tags/TechNews" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>TechNews</span></a> <a href="https://hear-me.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://hear-me.social/tags/AICommunity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AICommunity</span></a> <a href="https://hear-me.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://hear-me.social/tags/AIModels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AIModels</span></a> <a href="https://hear-me.social/tags/HuggingFace" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>HuggingFace</span></a> <br><a href="https://hear-me.social/tags/DeepSeek" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepSeek</span></a> <a href="https://hear-me.social/tags/DeepSeekV3" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepSeekV3</span></a></p>
Dr. Carlotta A. Berry, PhD<p><a href="https://blacktwitter.io/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://blacktwitter.io/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://blacktwitter.io/tags/BiasInAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BiasInAI</span></a> <a href="https://blacktwitter.io/tags/STEMSaturday" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>STEMSaturday</span></a> <a href="https://blacktwitter.io/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://blacktwitter.io/tags/ComputerVision" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ComputerVision</span></a> <a href="https://blacktwitter.io/tags/Robotics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Robotics</span></a> <a href="https://blacktwitter.io/tags/ReinforcementLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ReinforcementLearning</span></a> </p><p>Meet the editors of "Mitigating Bias in Machine Learning" Dr. Carlotta Berry and Dr. Brandeis Hill Marshall (Brandeis Marshall, PhD) <br>This practical guide shows, step by step, how to use machine learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender.<br>On Sale On Amazon <a href="https://a.co/d/dtMizVH" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="">a.co/d/dtMizVH</span><span class="invisible"></span></a></p>
Lord Caramac the Clueless, KSC<p><span class="h-card" translate="no"><a href="https://mastodon.social/@mcc" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>mcc</span></a></span> <a href="https://discordian.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> based software has been in use for quite some time now. We have seen all those toys like real-time video filters, image enhancers/upscalers, all that is basically the same thing as an image generator, the only new trick is coupling the image model with a language model and using random noise as input. Instead of giving the machine something ugly to prettify, you give it some grainy grey salt and pepper randomness like an analogue television tuned to a dead channel and tell it what kind of patterns to search for and amplify in that noise. <br>And LLMs are really just autocomplete on steroids. They literally just predict the next word and then the next one after that, just the next word that leads down one of the nearest pathways of high enough probability. It's a billion-dimensional landscape of language, but it doesn't know anything, it just has memorised everything and built a map of all the common patterns in all kinds of texts and how likely they are to occur in relation to all the preceding text. <br>It's just because LLMs have become quite good at producing text that looks like it has been written by a human being, people tend to believe they are actually intelligent. In fact, an <a href="https://discordian.social/tags/LLM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LLM</span></a> is just a <a href="https://discordian.social/tags/ChineseRoom" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ChineseRoom</span></a> --no mind in there, just statistical rules about language.</p><p>The trick is to make models smaller and more lightweight, training them on much smaller, human curated, high quality, data sets, resulting in software that can be run on low-spec hardware like a smartphone or a laptop and still produce decent results. The training data sets can be managed by volunteer online communities, and people can help training those models by having their computers donate computing power, crunching numbers for the community open source AI. <br>There isn't any money to be made that way, just simple AI tools that can be used by anybody with a laptop, no Internet needed, that's why all the focus is on the humongous ML models instead. Models that need huge data centres for their training, are completely closed proprietary systems, and only run on the servers of their owners, forcing everybody to pay rent for their usage, payable in money or data, everyone doing business in machine learning is trying to get the world addicted to their stuff. Small standalone ML models trained for a more specific purpose can be made much more energy efficient and also quite often much more useful and reliable. Unlike the blockchain, for which few serious use cases exist outside of recording who "owns" some huge number, machine learning can actually be used to solve problems for which humans use their intelligence. </p><p>However, machine learning forces us to rethink the entire concept of "intellectual property". IMHO, it's just bonkers that somebody can claim to own a piece of information. As soon as anything is out, you can't stop anybody from using it in any way they like. You can't stop anybody from making hundreds of copies of photos, cutting them to pieces and reassembling them to collages. You also can't stop anybody from downloading images from the Internet or grabbing them from video and training <a href="https://discordian.social/tags/StableDiffusion" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>StableDiffusion</span></a> models on those. You can't stop people from training fun sized LLMs on the ebook collections on their hard drives. The technology is out there, people know how to use it, they will use it and not care very much whether it is legal or not. Instead of trying to get the AI companies to pay for their unlicensed use of data, maybe we should just declare all AI research outside of intellectual property rights, putting all the resulting AI software in the public domain, and demand all source code to be public, free, and open. Also, nothing generated by any of those models should ever become anybody's intellectual property. THAT would be nice. Make it so that any AI which ever broke or bent any copyrights during training automatically turns into a public domain black hole which sucks everything it touches into the public domain. Let people generate as many AI hallucinations as they like, just tell them that they don't own the results, or rather, everybody does. Intellectual property sucks, anyway, even more than physical private property. If AI companies can't create I.P. based monopolies, they will never make any money, so they'll just fold if they are forced to publish everything free of charge, free to use.</p>
Lord Caramac the Clueless, KSC<p><span class="h-card" translate="no"><a href="https://mastodon.social/@mcc" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>mcc</span></a></span> It's not that <a href="https://discordian.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> isn't real, but people are rather unaware of what "artifical intelligence" is. AI is a term that is and has always been a branding, a label used for marketing. It's nothing more that a bunch of several branches of computer science that are about solving problems with computers for which humans need intelligence. The idea of a hypothetical Artificial General Intelligence (AGI), an artificial mind that is as intelligent as a human or even superintelligent, has been around for as long as programmable universal computers, but it is basically just a myth, just a prophecy; a bunch of AI researchers from different branches of the AI research tree have been dreaming of the homunculus growing from their respective branch any time soon. For the last 15 years or so, it has been the <a href="https://discordian.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> branch; a long time ago when I was little, it was the <a href="https://discordian.social/tags/ExpertSystem" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ExpertSystem</span></a> branch. Evolutionary algorithms might get back into the spotlight next, since machine learning is running out of steam, using bigger and bigger models and datasets for diminishing returns won't go on for very much longer. Basically, there are those who want to build an abstract model of a mind based upon philosophical theories of what intelligence might be, then there are those who want to model something resembling a brain with simple linear algebra, basically building huge billion-dimensional tensors and labelling them "artificial neural networks", and then there are the people who think you need a body and an environment with which you interact in order to become intelligent, and that the best way to become intelligent is some sort of artificial life that evolves. They are the ones who let algorithms "mutate" and then select those mutations that work better than the original one. They are the ones who build tiny robots and help them "evolve". </p><p>Well, with our current machine learning models and hardware, we won't get very much closer to anything like the human brain because an artificial neural network of that capacity would need a ludicrous amount of power and resources, we wouldn't be able to run any other software on any computer whatsoever on this planet because they all would be running a single instance of that artificial intelligence, and it still wouldn't be enough by several orders of magnitude. We would need all the power plants on this planet a thousand times over to do what a single human brain does powered by a piece of chocolate cake and a cup of tea. Unless there is some significant breakthrough very soon, an artificial neural network that rivals a human brain isn't going to happen anytime soon. Besides, I'm with the artificial life people, I don't believe a mind in a box is even possible, you need agency in the real world in order to become intelligent.</p>
𝕂𝚞𝚋𝚒𝚔ℙ𝚒𝚡𝚎𝚕<p>🧵 …da bin ich wohl nicht die einzige Person, die KI auch als Missbrauchsmittel zur Machterhabung sieht, wie schon oben mehrfach erwähnt. Diesmal ist es wirklich eine Fachperson und alles andere als verschwörerisch.</p><p>«„Vater des Deep Learning“ warnt vor Mächtigen, die die KI missbrauchen könnten»</p><p>🤖 <a href="https://t3n.de/news/vater-des-deep-learning-warnt-vor-maechtigen-die-die-ki-missbrauchen-koennten-1659720/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">t3n.de/news/vater-des-deep-lea</span><span class="invisible">rning-warnt-vor-maechtigen-die-die-ki-missbrauchen-koennten-1659720/</span></a></p><p><a href="https://chaos.social/tags/ki" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ki</span></a> <a href="https://chaos.social/tags/missbrauch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>missbrauch</span></a> <a href="https://chaos.social/tags/macht" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>macht</span></a> <a href="https://chaos.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> <a href="https://chaos.social/tags/machtmissbrauch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machtmissbrauch</span></a> <a href="https://chaos.social/tags/fachkritik" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>fachkritik</span></a> <a href="https://chaos.social/tags/openai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>openai</span></a></p>
Michael Paulino<p>Train your deep learning models with ease on huggingface.com Fine-tune pre-trained models & transfer learning techniques for various applications. <a href="https://mastodon.social/tags/HuggingFace" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>HuggingFace</span></a> <a href="https://mastodon.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.social/tags/MLCommunity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MLCommunity</span></a></p>
Greg Lloyd<p>“Li writes. “[in 2011] If ImageNet was a bet, it was time to start wondering if we’d lost.”</p><p>But when Li reluctantly staged the competition a third time in 2012, the results were totally different. Geoff Hinton’s team was the first to submit a model based on a deep neural network…</p><p>Li’s initial reaction was incredulity: “Most of us saw the neural network as a dusty artifact encased in glass and protected by velvet ropes.”</p><p>⭐️ <a href="https://federate.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> <a href="https://federate.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://federate.social/tags/history" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>history</span></a> <a href="https://mastodon.social/@arstechnica/113464229922836718" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">mastodon.social/@arstechnica/1</span><span class="invisible">13464229922836718</span></a></p>
Coach Pāṇini ®<p>I keep forgetting about the impending bubble collapse that was going to get blamed on <a href="https://mastodon.world/tags/KamalaHarris" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KamalaHarris</span></a>:</p><p>A few days ago, the well-known venture capitalist <a href="https://mastodon.world/tags/MarcAndreesen" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MarcAndreesen</span></a> started to spill the beans, saying on a podcast “we're increasing [graphics processing units] at the same rate, we're not getting the intelligent improvements at all out of it” – which is basically VC-ese for “<a href="https://mastodon.world/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> is hitting a wall.”<br><a href="https://garymarcus.substack.com/p/confirmed-llms-have-indeed-reached?r=8tdk6&utm_campaign=post&utm_medium=web&triedRedirect=true" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">garymarcus.substack.com/p/conf</span><span class="invisible">irmed-llms-have-indeed-reached?r=8tdk6&utm_campaign=post&utm_medium=web&triedRedirect=true</span></a></p>
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