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#slms — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #slms, aggregated by home.social.

  1. MFOS Sound Lab Mini-Synth PLUS

    The MFOS Sound Lab Mini-Synth PLUS (SMD version) is an Eurorack adaptation of Ray Wilson's classic Sound Lab Mini-Synth PLUS, itself a substantially enhanced evolution of the original Sound Lab Mini-Synth (SLMS). This conversion is part of the official effort by SynthCube to bring the Music From Outer Space (MFOS) analog synthesizer designs into the Eurorack modular format. […]

    davidhaillant.com/mfos-sound-l

  2. Small Language Models (SLMs) represent a shift toward ultra-efficient, privacy-preserving AI that can run locally and offline. For businesses, that means lower latency, reduced infrastructure costs, and stronger data protection. Dive into practical implications and where SLMs fit into your AI strategy: wix.to/NWrnNyX

    #AI
    #SLMs
    #EdgeAI
    #Innovation
    #DataPrivacy
    #MachineLearning

  3. Small Language Models (SLMs) represent a shift toward ultra-efficient, privacy-preserving AI that can run locally and offline. For businesses, that means lower latency, reduced infrastructure costs, and stronger data protection. Dive into practical implications and where SLMs fit into your AI strategy: wix.to/NWrnNyX

    #AI
    #SLMs
    #EdgeAI
    #Innovation
    #DataPrivacy
    #MachineLearning

  4. Small Language Models (SLMs) represent a shift toward ultra-efficient, privacy-preserving AI that can run locally and offline. For businesses, that means lower latency, reduced infrastructure costs, and stronger data protection. Dive into practical implications and where SLMs fit into your AI strategy: wix.to/NWrnNyX






  5. Small Language Models (SLMs) represent a shift toward ultra-efficient, privacy-preserving AI that can run locally and offline. For businesses, that means lower latency, reduced infrastructure costs, and stronger data protection. Dive into practical implications and where SLMs fit into your AI strategy: wix.to/NWrnNyX

    #AI
    #SLMs
    #EdgeAI
    #Innovation
    #DataPrivacy
    #MachineLearning

  6. Small Language Models (SLMs) represent a shift toward ultra-efficient, privacy-preserving AI that can run locally and offline. For businesses, that means lower latency, reduced infrastructure costs, and stronger data protection. Dive into practical implications and where SLMs fit into your AI strategy: wix.to/NWrnNyX

    #AI
    #SLMs
    #EdgeAI
    #Innovation
    #DataPrivacy
    #MachineLearning

  7. OwnAether Personal AI Operating Systems- What if your entire digital life — your work, your income, your creativity, your health, your automation, your business — was orchestrated by a single intelligent layer that learns you, works for you, and evolves with you?

    medium.com/@ownaether/the-pers

    #AI #PersonalAI #IndividualAI #MyAI #YourAI #LocalAI #DesktopAI #AIApps #PrivateAI #LLMs #SLMs #AIModels #PersonalAIAssistant #PersonalAIApp

  8. OwnAether Personal AI Operating Systems- What if your entire digital life — your work, your income, your creativity, your health, your automation, your business — was orchestrated by a single intelligent layer that learns you, works for you, and evolves with you?

    medium.com/@ownaether/the-pers

    #AI #PersonalAI #IndividualAI #MyAI #YourAI #LocalAI #DesktopAI #AIApps #PrivateAI #LLMs #SLMs #AIModels #PersonalAIAssistant #PersonalAIApp

  9. OwnAether Personal AI Operating Systems- What if your entire digital life — your work, your income, your creativity, your health, your automation, your business — was orchestrated by a single intelligent layer that learns you, works for you, and evolves with you?

    medium.com/@ownaether/the-pers

    #AI #PersonalAI #IndividualAI #MyAI #YourAI #LocalAI #DesktopAI #AIApps #PrivateAI #LLMs #SLMs #AIModels #PersonalAIAssistant #PersonalAIApp

  10. OwnAether Personal AI Operating Systems- What if your entire digital life — your work, your income, your creativity, your health, your automation, your business — was orchestrated by a single intelligent layer that learns you, works for you, and evolves with you?

    medium.com/@ownaether/the-pers

    #AI #PersonalAI #IndividualAI #MyAI #YourAI #LocalAI #DesktopAI #AIApps #PrivateAI #LLMs #SLMs #AIModels #PersonalAIAssistant #PersonalAIApp

  11. OwnAether Personal AI Operating Systems- What if your entire digital life — your work, your income, your creativity, your health, your automation, your business — was orchestrated by a single intelligent layer that learns you, works for you, and evolves with you?

    medium.com/@ownaether/the-pers

    #AI #PersonalAI #IndividualAI #MyAI #YourAI #LocalAI #DesktopAI #AIApps #PrivateAI #LLMs #SLMs #AIModels #PersonalAIAssistant #PersonalAIApp

  12. “The Saving Voices Project recently built a speech AI system for the Indigenous Soliga tribe in southern India. As younger members migrated to the cities for jobs, elders in the community feared losing their language. With a small number of speakers, no written script, and no internet access, commercial speech technology was not an option. The Saving Voices Project, along with the Indian Institute of Information Technology, Dharwad, custom-built cheap text-to-speech AI models that run on low-powered devices, and can operate offline for long periods.

    The model is replicable for Indigenous language preservation globally, Sathiaseelan said.

    “With just five hours of voice data, we were able to build a voice model for the Soliga by prioritizing community ownership, and with frugal, deployable technology,” he said.

    Unlike the compute-heavy AI models developed by Silicon Valley, the smaller models being built in India, Indonesia, and elsewhere can run on low-end devices and low-bandwidth networks, and be deployed in sectors such as agriculture, health-care, and education. The models are not only cost-efficient, they also have a lower impact on the environment, Sathiaseelan said.

    “This is perhaps the most important dimension of frugal AI,” he said. “It is about building leaner, more efficient systems from the ground up. By design, the systems use less compute, less memory, and less energy, which directly translates into a smaller carbon footprint.”“

    restofworld.org/2026/frugal-ai

    #AI #SLMs #FrugalAI #GlobalSouth #BigTech

  13. “The Saving Voices Project recently built a speech AI system for the Indigenous Soliga tribe in southern India. As younger members migrated to the cities for jobs, elders in the community feared losing their language. With a small number of speakers, no written script, and no internet access, commercial speech technology was not an option. The Saving Voices Project, along with the Indian Institute of Information Technology, Dharwad, custom-built cheap text-to-speech AI models that run on low-powered devices, and can operate offline for long periods.

    The model is replicable for Indigenous language preservation globally, Sathiaseelan said.

    “With just five hours of voice data, we were able to build a voice model for the Soliga by prioritizing community ownership, and with frugal, deployable technology,” he said.

    Unlike the compute-heavy AI models developed by Silicon Valley, the smaller models being built in India, Indonesia, and elsewhere can run on low-end devices and low-bandwidth networks, and be deployed in sectors such as agriculture, health-care, and education. The models are not only cost-efficient, they also have a lower impact on the environment, Sathiaseelan said.

    “This is perhaps the most important dimension of frugal AI,” he said. “It is about building leaner, more efficient systems from the ground up. By design, the systems use less compute, less memory, and less energy, which directly translates into a smaller carbon footprint.”“

    restofworld.org/2026/frugal-ai

    #AI #SLMs #FrugalAI #GlobalSouth #BigTech

  14. “The Saving Voices Project recently built a speech AI system for the Indigenous Soliga tribe in southern India. As younger members migrated to the cities for jobs, elders in the community feared losing their language. With a small number of speakers, no written script, and no internet access, commercial speech technology was not an option. The Saving Voices Project, along with the Indian Institute of Information Technology, Dharwad, custom-built cheap text-to-speech AI models that run on low-powered devices, and can operate offline for long periods.

    The model is replicable for Indigenous language preservation globally, Sathiaseelan said.

    “With just five hours of voice data, we were able to build a voice model for the Soliga by prioritizing community ownership, and with frugal, deployable technology,” he said.

    Unlike the compute-heavy AI models developed by Silicon Valley, the smaller models being built in India, Indonesia, and elsewhere can run on low-end devices and low-bandwidth networks, and be deployed in sectors such as agriculture, health-care, and education. The models are not only cost-efficient, they also have a lower impact on the environment, Sathiaseelan said.

    “This is perhaps the most important dimension of frugal AI,” he said. “It is about building leaner, more efficient systems from the ground up. By design, the systems use less compute, less memory, and less energy, which directly translates into a smaller carbon footprint.”“

    restofworld.org/2026/frugal-ai

    #AI #SLMs #FrugalAI #GlobalSouth #BigTech

  15. “The Saving Voices Project recently built a speech AI system for the Indigenous Soliga tribe in southern India. As younger members migrated to the cities for jobs, elders in the community feared losing their language. With a small number of speakers, no written script, and no internet access, commercial speech technology was not an option. The Saving Voices Project, along with the Indian Institute of Information Technology, Dharwad, custom-built cheap text-to-speech AI models that run on low-powered devices, and can operate offline for long periods.

    The model is replicable for Indigenous language preservation globally, Sathiaseelan said.

    “With just five hours of voice data, we were able to build a voice model for the Soliga by prioritizing community ownership, and with frugal, deployable technology,” he said.

    Unlike the compute-heavy AI models developed by Silicon Valley, the smaller models being built in India, Indonesia, and elsewhere can run on low-end devices and low-bandwidth networks, and be deployed in sectors such as agriculture, health-care, and education. The models are not only cost-efficient, they also have a lower impact on the environment, Sathiaseelan said.

    “This is perhaps the most important dimension of frugal AI,” he said. “It is about building leaner, more efficient systems from the ground up. By design, the systems use less compute, less memory, and less energy, which directly translates into a smaller carbon footprint.”“

    restofworld.org/2026/frugal-ai

    #AI #SLMs #FrugalAI #GlobalSouth #BigTech

  16. “The Saving Voices Project recently built a speech AI system for the Indigenous Soliga tribe in southern India. As younger members migrated to the cities for jobs, elders in the community feared losing their language. With a small number of speakers, no written script, and no internet access, commercial speech technology was not an option. The Saving Voices Project, along with the Indian Institute of Information Technology, Dharwad, custom-built cheap text-to-speech AI models that run on low-powered devices, and can operate offline for long periods.

    The model is replicable for Indigenous language preservation globally, Sathiaseelan said.

    “With just five hours of voice data, we were able to build a voice model for the Soliga by prioritizing community ownership, and with frugal, deployable technology,” he said.

    Unlike the compute-heavy AI models developed by Silicon Valley, the smaller models being built in India, Indonesia, and elsewhere can run on low-end devices and low-bandwidth networks, and be deployed in sectors such as agriculture, health-care, and education. The models are not only cost-efficient, they also have a lower impact on the environment, Sathiaseelan said.

    “This is perhaps the most important dimension of frugal AI,” he said. “It is about building leaner, more efficient systems from the ground up. By design, the systems use less compute, less memory, and less energy, which directly translates into a smaller carbon footprint.”“

    restofworld.org/2026/frugal-ai

    #AI #SLMs #FrugalAI #GlobalSouth #BigTech

  17. "If the strengths of A.I. are to truly be harnessed, the tech industry should stop focusing so heavily on these one-size-fits-all tools, and instead concentrate on narrow, specialized A.I. tools engineered for particular problems. Because, frankly, they’re often more effective.

    Until the advent of chatbots, most A.I. developers focused on building special-purpose systems, for things like playing chess or recommending books and movies to consumers. These systems were not nearly as sexy as talking to a chatbot, and each project often took years to get right. But they were often more reliable than today’s generative A.I. tools, because they didn’t try to learn everything from scratch and were often engineered on the basis of expert knowledge.

    Take chess. If you ask a large language model (the kind of A.I. that powers a chatbot like ChatGPT) to play a game of chess, it struggles to play well and often makes illegal moves, never fully grasping the rules of the game, even after exposure to huge amounts of relevant training data.

    Special-purpose programs for chess, in contrast, are programmed from the outset to follow a built-in set of rules, and structured around core notions such as board structure and a tree of possible moves. Such systems never make illegal moves, and the best special-purpose chess systems can easily beat even the most skilled humans. Remarkably, an Atari 2600, using custom A.I. software built in the 1970s, was recently reported to have beaten a large language model."

    nytimes.com/2025/10/16/opinion

    #AI #GenerativeAI #LLMs #Chatbots #SLMs

  18. "If the strengths of A.I. are to truly be harnessed, the tech industry should stop focusing so heavily on these one-size-fits-all tools, and instead concentrate on narrow, specialized A.I. tools engineered for particular problems. Because, frankly, they’re often more effective.

    Until the advent of chatbots, most A.I. developers focused on building special-purpose systems, for things like playing chess or recommending books and movies to consumers. These systems were not nearly as sexy as talking to a chatbot, and each project often took years to get right. But they were often more reliable than today’s generative A.I. tools, because they didn’t try to learn everything from scratch and were often engineered on the basis of expert knowledge.

    Take chess. If you ask a large language model (the kind of A.I. that powers a chatbot like ChatGPT) to play a game of chess, it struggles to play well and often makes illegal moves, never fully grasping the rules of the game, even after exposure to huge amounts of relevant training data.

    Special-purpose programs for chess, in contrast, are programmed from the outset to follow a built-in set of rules, and structured around core notions such as board structure and a tree of possible moves. Such systems never make illegal moves, and the best special-purpose chess systems can easily beat even the most skilled humans. Remarkably, an Atari 2600, using custom A.I. software built in the 1970s, was recently reported to have beaten a large language model."

    nytimes.com/2025/10/16/opinion

    #AI #GenerativeAI #LLMs #Chatbots #SLMs

  19. "If the strengths of A.I. are to truly be harnessed, the tech industry should stop focusing so heavily on these one-size-fits-all tools, and instead concentrate on narrow, specialized A.I. tools engineered for particular problems. Because, frankly, they’re often more effective.

    Until the advent of chatbots, most A.I. developers focused on building special-purpose systems, for things like playing chess or recommending books and movies to consumers. These systems were not nearly as sexy as talking to a chatbot, and each project often took years to get right. But they were often more reliable than today’s generative A.I. tools, because they didn’t try to learn everything from scratch and were often engineered on the basis of expert knowledge.

    Take chess. If you ask a large language model (the kind of A.I. that powers a chatbot like ChatGPT) to play a game of chess, it struggles to play well and often makes illegal moves, never fully grasping the rules of the game, even after exposure to huge amounts of relevant training data.

    Special-purpose programs for chess, in contrast, are programmed from the outset to follow a built-in set of rules, and structured around core notions such as board structure and a tree of possible moves. Such systems never make illegal moves, and the best special-purpose chess systems can easily beat even the most skilled humans. Remarkably, an Atari 2600, using custom A.I. software built in the 1970s, was recently reported to have beaten a large language model."

    nytimes.com/2025/10/16/opinion

    #AI #GenerativeAI #LLMs #Chatbots #SLMs

  20. "If the strengths of A.I. are to truly be harnessed, the tech industry should stop focusing so heavily on these one-size-fits-all tools, and instead concentrate on narrow, specialized A.I. tools engineered for particular problems. Because, frankly, they’re often more effective.

    Until the advent of chatbots, most A.I. developers focused on building special-purpose systems, for things like playing chess or recommending books and movies to consumers. These systems were not nearly as sexy as talking to a chatbot, and each project often took years to get right. But they were often more reliable than today’s generative A.I. tools, because they didn’t try to learn everything from scratch and were often engineered on the basis of expert knowledge.

    Take chess. If you ask a large language model (the kind of A.I. that powers a chatbot like ChatGPT) to play a game of chess, it struggles to play well and often makes illegal moves, never fully grasping the rules of the game, even after exposure to huge amounts of relevant training data.

    Special-purpose programs for chess, in contrast, are programmed from the outset to follow a built-in set of rules, and structured around core notions such as board structure and a tree of possible moves. Such systems never make illegal moves, and the best special-purpose chess systems can easily beat even the most skilled humans. Remarkably, an Atari 2600, using custom A.I. software built in the 1970s, was recently reported to have beaten a large language model."

    nytimes.com/2025/10/16/opinion

    #AI #GenerativeAI #LLMs #Chatbots #SLMs

  21. "If the strengths of A.I. are to truly be harnessed, the tech industry should stop focusing so heavily on these one-size-fits-all tools, and instead concentrate on narrow, specialized A.I. tools engineered for particular problems. Because, frankly, they’re often more effective.

    Until the advent of chatbots, most A.I. developers focused on building special-purpose systems, for things like playing chess or recommending books and movies to consumers. These systems were not nearly as sexy as talking to a chatbot, and each project often took years to get right. But they were often more reliable than today’s generative A.I. tools, because they didn’t try to learn everything from scratch and were often engineered on the basis of expert knowledge.

    Take chess. If you ask a large language model (the kind of A.I. that powers a chatbot like ChatGPT) to play a game of chess, it struggles to play well and often makes illegal moves, never fully grasping the rules of the game, even after exposure to huge amounts of relevant training data.

    Special-purpose programs for chess, in contrast, are programmed from the outset to follow a built-in set of rules, and structured around core notions such as board structure and a tree of possible moves. Such systems never make illegal moves, and the best special-purpose chess systems can easily beat even the most skilled humans. Remarkably, an Atari 2600, using custom A.I. software built in the 1970s, was recently reported to have beaten a large language model."

    nytimes.com/2025/10/16/opinion

    #AI #GenerativeAI #LLMs #Chatbots #SLMs

  22. Is Faith in the supposed “God-like” powers of large language models (LLMs) waning as businesses and developers shift their focus to smaller, more nimble alternatives?

    This trend suggests a significant change in the AI landscape, with important implications for both the tech giants at the forefront and those, like Apple, that have taken a more cautious approach.

    neurodoctor.com/2025/09/09/fai
    #ai #artificialintelligence #llm #slms #apple #nvidia #openai

  23. Is Faith in the supposed “God-like” powers of large language models (LLMs) waning as businesses and developers shift their focus to smaller, more nimble alternatives?

    This trend suggests a significant change in the AI landscape, with important implications for both the tech giants at the forefront and those, like Apple, that have taken a more cautious approach.

    neurodoctor.com/2025/09/09/fai
    #ai #artificialintelligence #llm #slms #apple #nvidia #openai

  24. Is Faith in the supposed “God-like” powers of large language models (LLMs) waning as businesses and developers shift their focus to smaller, more nimble alternatives?

    This trend suggests a significant change in the AI landscape, with important implications for both the tech giants at the forefront and those, like Apple, that have taken a more cautious approach.

    neurodoctor.com/2025/09/09/fai
    #ai #artificialintelligence #llm #slms #apple #nvidia #openai

  25. Is Faith in the supposed “God-like” powers of large language models (LLMs) waning as businesses and developers shift their focus to smaller, more nimble alternatives?

    This trend suggests a significant change in the AI landscape, with important implications for both the tech giants at the forefront and those, like Apple, that have taken a more cautious approach.

    neurodoctor.com/2025/09/09/fai
    #ai #artificialintelligence #llm #slms #apple #nvidia #openai

  26. Is Faith in the supposed “God-like” powers of large language models (LLMs) waning as businesses and developers shift their focus to smaller, more nimble alternatives?

    This trend suggests a significant change in the AI landscape, with important implications for both the tech giants at the forefront and those, like Apple, that have taken a more cautious approach.

    neurodoctor.com/2025/09/09/fai
    #ai #artificialintelligence #llm #slms #apple #nvidia #openai

  27. "AI-powered influence operations can now be executed end-to-end on commodity hardware. We show that small language models produce coherent, persona-driven political messaging and can be evaluated automatically without human raters. Two behavioural findings emerge. First, persona-over-model: persona design explains behaviour more than model identity. Second, engagement as a stressor: when replies must counter-arguments, ideological adherence strengthens and the prevalence of extreme content increases. We demonstrate that fully automated influence-content production is within reach of both large and small actors. Consequently, defence should shift from restricting model access towards conversation-centric detection and disruption of campaigns and coordination infrastructure. Paradoxically, the very consistency that enables these operations also provides a detection signature."

    arxiv.org/html/2508.20186v1

    #AI #GenerativeAI #LLMs #Chatbots #Propaganda #AIPropaganda #Disinformation #SLMs

  28. "AI-powered influence operations can now be executed end-to-end on commodity hardware. We show that small language models produce coherent, persona-driven political messaging and can be evaluated automatically without human raters. Two behavioural findings emerge. First, persona-over-model: persona design explains behaviour more than model identity. Second, engagement as a stressor: when replies must counter-arguments, ideological adherence strengthens and the prevalence of extreme content increases. We demonstrate that fully automated influence-content production is within reach of both large and small actors. Consequently, defence should shift from restricting model access towards conversation-centric detection and disruption of campaigns and coordination infrastructure. Paradoxically, the very consistency that enables these operations also provides a detection signature."

    arxiv.org/html/2508.20186v1

    #AI #GenerativeAI #LLMs #Chatbots #Propaganda #AIPropaganda #Disinformation #SLMs

  29. "AI-powered influence operations can now be executed end-to-end on commodity hardware. We show that small language models produce coherent, persona-driven political messaging and can be evaluated automatically without human raters. Two behavioural findings emerge. First, persona-over-model: persona design explains behaviour more than model identity. Second, engagement as a stressor: when replies must counter-arguments, ideological adherence strengthens and the prevalence of extreme content increases. We demonstrate that fully automated influence-content production is within reach of both large and small actors. Consequently, defence should shift from restricting model access towards conversation-centric detection and disruption of campaigns and coordination infrastructure. Paradoxically, the very consistency that enables these operations also provides a detection signature."

    arxiv.org/html/2508.20186v1

    #AI #GenerativeAI #LLMs #Chatbots #Propaganda #AIPropaganda #Disinformation #SLMs

  30. "AI-powered influence operations can now be executed end-to-end on commodity hardware. We show that small language models produce coherent, persona-driven political messaging and can be evaluated automatically without human raters. Two behavioural findings emerge. First, persona-over-model: persona design explains behaviour more than model identity. Second, engagement as a stressor: when replies must counter-arguments, ideological adherence strengthens and the prevalence of extreme content increases. We demonstrate that fully automated influence-content production is within reach of both large and small actors. Consequently, defence should shift from restricting model access towards conversation-centric detection and disruption of campaigns and coordination infrastructure. Paradoxically, the very consistency that enables these operations also provides a detection signature."

    arxiv.org/html/2508.20186v1

    #AI #GenerativeAI #LLMs #Chatbots #Propaganda #AIPropaganda #Disinformation #SLMs

  31. "AI-powered influence operations can now be executed end-to-end on commodity hardware. We show that small language models produce coherent, persona-driven political messaging and can be evaluated automatically without human raters. Two behavioural findings emerge. First, persona-over-model: persona design explains behaviour more than model identity. Second, engagement as a stressor: when replies must counter-arguments, ideological adherence strengthens and the prevalence of extreme content increases. We demonstrate that fully automated influence-content production is within reach of both large and small actors. Consequently, defence should shift from restricting model access towards conversation-centric detection and disruption of campaigns and coordination infrastructure. Paradoxically, the very consistency that enables these operations also provides a detection signature."

    arxiv.org/html/2508.20186v1

    #AI #GenerativeAI #LLMs #Chatbots #Propaganda #AIPropaganda #Disinformation #SLMs

  32. 🧠 Il futuro dell’#AI agentica è small? 

    💡Secondo NVIDIA Research, gli Small Language Models (#SLMs) offrono una combinazione vincente.

    👉 I dettagli: linkedin.com/posts/alessiopoma

    ___ 

    ✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: bit.ly/newsletter-alessiopomar 

    #AI #GenAI #GenerativeAI #IntelligenzaArtificiale #LLM 

  33. 🧠 Il futuro dell’#AI agentica è small? 

    💡Secondo NVIDIA Research, gli Small Language Models (#SLMs) offrono una combinazione vincente.

    👉 I dettagli: linkedin.com/posts/alessiopoma

    ___ 

    ✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: bit.ly/newsletter-alessiopomar 

    #AI #GenAI #GenerativeAI #IntelligenzaArtificiale #LLM 

  34. 🧠 Il futuro dell’#AI agentica è small? 

    💡Secondo NVIDIA Research, gli Small Language Models (#SLMs) offrono una combinazione vincente.

    👉 I dettagli: linkedin.com/posts/alessiopoma

    ___ 

    ✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: bit.ly/newsletter-alessiopomar 

    #AI #GenAI #GenerativeAI #IntelligenzaArtificiale #LLM 

  35. 🧠 Il futuro dell’#AI agentica è small? 

    💡Secondo NVIDIA Research, gli Small Language Models (#SLMs) offrono una combinazione vincente.

    👉 I dettagli: linkedin.com/posts/alessiopoma

    ___ 

    ✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: bit.ly/newsletter-alessiopomar 

    #AI #GenAI #GenerativeAI #IntelligenzaArtificiale #LLM 

  36. 🧠 Il futuro dell’#AI agentica è small? 

    💡Secondo NVIDIA Research, gli Small Language Models (#SLMs) offrono una combinazione vincente.

    👉 I dettagli: linkedin.com/posts/alessiopoma

    ___ 

    ✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: bit.ly/newsletter-alessiopomar 

    #AI #GenAI #GenerativeAI #IntelligenzaArtificiale #LLM 

  37. 🚀 Why pay more for cloud AI when smarter AI fits in your watch?
    Discover how Small Language Models are quietly outperforming LLMs —
    • 8X faster
    • 90% cheaper
    • 100% offline 🤯

    From Tesla to smart clinics, this is the AI story no one's telling — yet.
    Read the full piece 👇
    🔗 medium.com/@rogt.x1997/8x-fast

    #EdgeAI #SLMs #TinyML #FutureReady
    medium.com/@rogt.x1997/8x-fast

  38. 🚀 Why pay more for cloud AI when smarter AI fits in your watch?
    Discover how Small Language Models are quietly outperforming LLMs —
    • 8X faster
    • 90% cheaper
    • 100% offline 🤯

    From Tesla to smart clinics, this is the AI story no one's telling — yet.
    Read the full piece 👇
    🔗 medium.com/@rogt.x1997/8x-fast

    #EdgeAI #SLMs #TinyML #FutureReady
    medium.com/@rogt.x1997/8x-fast