#watsonx — Public Fediverse posts

#ibm #watsonx #aiagent #aigovernance #agentic #aisecurity

Beth Pariseau @[email protected] · 2026-02-05 · 15:09 UTC

Suzanne Livingston has worked at IBM for 19 years, most recently in the role of vice president overseeing product management for the #IBM #watsonx Orchestrate #AIagent platform. She says enterprises must strike a balance between #AIgovernance and trying to force every workload into one platform – or to be #agentic at all. Going forward, managing AI agents will require new kinds of human-to-AI and human-to-human collaboration, according to Livingston, that the industry is just learning about.

In today’s episode, we’ll cover…

-- Watsonx Orchestrate support for third-party AI agents

-- Unsolved #AIsecurity problems

-- How IBM customers are approaching AI governance

-- AI's influence on the future of work

and more!

#ibm #watsonx #aiagent #aigovernance #agentic #aisecurity

Beth Pariseau @BPariseau · 2026-02-05 · 15:09 UTC

Suzanne Livingston has worked at IBM for 19 years, most recently in the role of vice president overseeing product management for the #IBM #watsonx Orchestrate #AIagent platform. She says enterprises must strike a balance between #AIgovernance and trying to force every workload into one platform – or to be #agentic at all. Going forward, managing AI agents will require new kinds of human-to-AI and human-to-human collaboration, according to Livingston, that the industry is just learning about.

In today’s episode, we’ll cover…

-- Watsonx Orchestrate support for third-party AI agents

-- Unsolved #AIsecurity problems

-- How IBM customers are approaching AI governance

-- AI's influence on the future of work

and more!

#ibm #watsonx #aiagent #aigovernance #agentic #aisecurity

Beth Pariseau @[email protected] · 2026-02-05 · 15:09 UTC

Suzanne Livingston has worked at IBM for 19 years, most recently in the role of vice president overseeing product management for the #IBM #watsonx Orchestrate #AIagent platform. She says enterprises must strike a balance between #AIgovernance and trying to force every workload into one platform – or to be #agentic at all. Going forward, managing AI agents will require new kinds of human-to-AI and human-to-human collaboration, according to Livingston, that the industry is just learning about.

In today’s episode, we’ll cover…

-- Watsonx Orchestrate support for third-party AI agents

-- Unsolved #AIsecurity problems

-- How IBM customers are approaching AI governance

-- AI's influence on the future of work

and more!

#aisecurity #agentic #aigovernance #aiagent #watsonx #ibm

Beth Pariseau @[email protected] · 2026-02-05 · 15:09 UTC

Suzanne Livingston has worked at IBM for 19 years, most recently in the role of vice president overseeing product management for the #IBM #watsonx Orchestrate #AIagent platform. She says enterprises must strike a balance between #AIgovernance and trying to force every workload into one platform – or to be #agentic at all. Going forward, managing AI agents will require new kinds of human-to-AI and human-to-human collaboration, according to Livingston, that the industry is just learning about.

In today’s episode, we’ll cover…

-- Watsonx Orchestrate support for third-party AI agents

-- Unsolved #AIsecurity problems

-- How IBM customers are approaching AI governance

-- AI's influence on the future of work

and more!

#ibm #watsonx #aiagent #aigovernance #agentic #aisecurity

:rss: Qiita - 人気の記事 @[email protected] · 2025-11-07 · 09:36 UTC

AI×BI　IBM watsonx BIを触ってみよう！
https://qiita.com/YokeSin/items/7839b58710803009cd48?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #AI #BI #IBM #watsonx #watsonxBI

#qiita #ai #bi #ibm #watsonx #watsonxbi

:rss: Qiita - 人気の記事 @[email protected] · 2025-11-07 · 09:36 UTC

AI×BI　IBM watsonx BIを触ってみよう！
https://qiita.com/YokeSin/items/7839b58710803009cd48?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #AI #BI #IBM #watsonx #watsonxBI

#qiita #ai #bi #ibm #watsonx #watsonxbi

RedPacket Security @[email protected] · 2025-08-30 · 14:30 UTC

CVE Alert: CVE-2025-0165 - IBM - watsonx Orchestrate Cartridge for IBM Cloud Pak for Data - https://www.redpacketsecurity.com/cve-alert-cve-2025-0165-ibm-watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data/

#OSINT #ThreatIntel #CyberSecurity #cve-2025-0165 #ibm #watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data

#osint #threatintel #cybersecurity #cve #ibm #watsonx

RedPacket Security @[email protected] · 2025-08-30 · 14:30 UTC

CVE Alert: CVE-2025-0165 - IBM - watsonx Orchestrate Cartridge for IBM Cloud Pak for Data - https://www.redpacketsecurity.com/cve-alert-cve-2025-0165-ibm-watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data/

#OSINT #ThreatIntel #CyberSecurity #cve-2025-0165 #ibm #watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data

#osint #threatintel #cybersecurity #cve #ibm #watsonx

RedPacket Security @[email protected] · 2025-08-30 · 14:30 UTC

CVE Alert: CVE-2025-0165 - IBM - watsonx Orchestrate Cartridge for IBM Cloud Pak for Data - https://www.redpacketsecurity.com/cve-alert-cve-2025-0165-ibm-watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data/

#OSINT #ThreatIntel #CyberSecurity #cve-2025-0165 #ibm #watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data

#watsonx #ibm #cve #cybersecurity #threatintel #osint

RedPacket Security @[email protected] · 2025-08-30 · 14:30 UTC

CVE Alert: CVE-2025-0165 - IBM - watsonx Orchestrate Cartridge for IBM Cloud Pak for Data - https://www.redpacketsecurity.com/cve-alert-cve-2025-0165-ibm-watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data/

#OSINT #ThreatIntel #CyberSecurity #cve-2025-0165 #ibm #watsonx-orchestrate-cartridge-for-ibm-cloud-pak-for-data

#osint #threatintel #cybersecurity #cve #ibm #watsonx

Global Threads @[email protected] · 2025-06-03 · 14:53 UTC

🤖 TECH
🔴 IBM Acquires Seek AI, Launches Watsonx Labs

🔸 IBM bought Seek AI, a startup enabling natural language data queries; price undisclosed.
🔸 Its tech powers Watsonx AI Labs, IBM’s new accelerator in NYC’s One Madison tower.
🔸 IBM plans to scale Seek AI and invest via IBM Ventures.
🔸 Labs will collaborate with NY universities on enterprise AI tools.

#ibm #seekai #watsonx #nyc #ai

Global Threads @[email protected] · 2025-06-03 · 14:53 UTC

🤖 TECH
🔴 IBM Acquires Seek AI, Launches Watsonx Labs

🔸 IBM bought Seek AI, a startup enabling natural language data queries; price undisclosed.
🔸 Its tech powers Watsonx AI Labs, IBM’s new accelerator in NYC’s One Madison tower.
🔸 IBM plans to scale Seek AI and invest via IBM Ventures.
🔸 Labs will collaborate with NY universities on enterprise AI tools.

#ibm #seekai #watsonx #nyc #ai

Global Threads @[email protected] · 2025-06-03 · 14:53 UTC

🤖 TECH
🔴 IBM Acquires Seek AI, Launches Watsonx Labs

🔸 IBM bought Seek AI, a startup enabling natural language data queries; price undisclosed.
🔸 Its tech powers Watsonx AI Labs, IBM’s new accelerator in NYC’s One Madison tower.
🔸 IBM plans to scale Seek AI and invest via IBM Ventures.
🔸 Labs will collaborate with NY universities on enterprise AI tools.

#ai #nyc #watsonx #seekai #ibm

Global Threads @[email protected] · 2025-06-03 · 14:53 UTC

🤖 TECH
🔴 IBM Acquires Seek AI, Launches Watsonx Labs

🔸 IBM bought Seek AI, a startup enabling natural language data queries; price undisclosed.
🔸 Its tech powers Watsonx AI Labs, IBM’s new accelerator in NYC’s One Madison tower.
🔸 IBM plans to scale Seek AI and invest via IBM Ventures.
🔸 Labs will collaborate with NY universities on enterprise AI tools.

#ibm #seekai #watsonx #nyc #ai

History Hackers｜歴史の中に生きる力 @[email protected] · 2025-05-07 · 21:00 UTC

AIMindUpdate News!
🚀⚡️💰 Automate tasks faster! IBM's watsonx Orchestrate gets an upgrade with new AI agent-building capabilities for enterprises. #IBM #AIagents #watsonx

Click here↓↓↓
https://aimindupdate.com/2025/05/08/ibm-revamps-watsonx-orchestrate-new-tools-for-ai-agent-building

#ibm #aiagents #watsonx

:rss: Qiita - 人気の記事 @[email protected] · 2025-04-23 · 12:05 UTC

【備忘録】watsonx.governanceのAPIキーとかとか
https://qiita.com/KwangsooLee/items/a4fb0d42e32fc15c82cf?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #watsonx

:rss: Qiita - 人気の記事 @[email protected] · 2025-04-23 · 12:05 UTC

【備忘録】watsonx.governanceのAPIキーとかとか
https://qiita.com/KwangsooLee/items/a4fb0d42e32fc15c82cf?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #watsonx

:rss: Qiita - 人気の記事 @[email protected] · 2025-04-23 · 12:05 UTC

【備忘録】watsonx.governanceのAPIキーとかとか
https://qiita.com/KwangsooLee/items/a4fb0d42e32fc15c82cf?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #watsonx

RS, Author, Novelist, Prosaist @[email protected] · 2025-01-06 · 20:22 UTC

AI [probably referring to a LLM] is not trained by professionals or a single end user, because it requires such huge amounts of input training data...

You are correct and you are incorrect.

From scratch finding data for pattern matching is tough and requires high performance engines, trade-offs, and money. But we stand on the backs of giants.

There are trained ethical LLMs, certified to be so and deep pockets to back the assertion and the necessary curation. They are not necessarily free. From those seeds AIs can be built to do the things of which I speak.

If IBM can do it (and they do; having gone to the training and hard sell, I know), Apple Intelligence could be built and use Apple engines as infrastructure. Big Blue's giant Z mainframes, which are blades in pretty artwork boxed server racks, are performant due to their custom chips, virtual system management, tuned I/O structure, and multitasking software. Apple chips are performant, custom, and cheaper for the end user. Apple Intelligence is likely Apple's WatsonX App-Killer that'll make the difference, and most certainly runs on Apple hardware increasingly running on renewables.

My point isn't so much building LLMs from scratch, but applications built on a platform and then trained from private user data and via user curation. If I implied otherwise, I wasn't clear. Sorry.

I assume Apple's LLMs are ethical. I also assume that Apple is exposing AI APIs for use by developers.

#LLM #Ibmz #AI #genAI #ethics #watsonx #ibm #Apple #intelligence #Writer #Author #Fiction #WritingCommunity #WritersOfMastodon #Programmer #Program #Application #Code #Coding

Cc: @vextaur

#llm #ibmz #ai #genai #ethics #watsonx

RS, Author, Novelist, Prosaist @[email protected] · 2025-01-06 · 20:22 UTC

AI [probably referring to a LLM] is not trained by professionals or a single end user, because it requires such huge amounts of input training data...

You are correct and you are incorrect.

From scratch finding data for pattern matching is tough and requires high performance engines, trade-offs, and money. But we stand on the backs of giants.

There are trained ethical LLMs, certified to be so and deep pockets to back the assertion and the necessary curation. They are not necessarily free. From those seeds AIs can be built to do the things of which I speak.

If IBM can do it (and they do; having gone to the training and hard sell, I know), Apple Intelligence could be built and use Apple engines as infrastructure. Big Blue's giant Z mainframes, which are blades in pretty artwork boxed server racks, are performant due to their custom chips, virtual system management, tuned I/O structure, and multitasking software. Apple chips are performant, custom, and cheaper for the end user. Apple Intelligence is likely Apple's WatsonX App-Killer that'll make the difference, and most certainly runs on Apple hardware increasingly running on renewables.

My point isn't so much building LLMs from scratch, but applications built on a platform and then trained from private user data and via user curation. If I implied otherwise, I wasn't clear. Sorry.

I assume Apple's LLMs are ethical. I also assume that Apple is exposing AI APIs for use by developers.

#LLM #Ibmz #AI #genAI #ethics #watsonx #ibm #Apple #intelligence #Writer #Author #Fiction #WritingCommunity #WritersOfMastodon #Programmer #Program #Application #Code #Coding

Cc: @vextaur

#llm #ibmz #ai #genai #ethics #watsonx

RS, Author, Novelist, Prosaist @[email protected] · 2025-01-06 · 20:22 UTC

AI [probably referring to a LLM] is not trained by professionals or a single end user, because it requires such huge amounts of input training data...

You are correct and you are incorrect.

From scratch finding data for pattern matching is tough and requires high performance engines, trade-offs, and money. But we stand on the backs of giants.

There are trained ethical LLMs, certified to be so and deep pockets to back the assertion and the necessary curation. They are not necessarily free. From those seeds AIs can be built to do the things of which I speak.

If IBM can do it (and they do; having gone to the training and hard sell, I know), Apple Intelligence could be built and use Apple engines as infrastructure. Big Blue's giant Z mainframes, which are blades in pretty artwork boxed server racks, are performant due to their custom chips, virtual system management, tuned I/O structure, and multitasking software. Apple chips are performant, custom, and cheaper for the end user. Apple Intelligence is likely Apple's WatsonX App-Killer that'll make the difference, and most certainly runs on Apple hardware increasingly running on renewables.

My point isn't so much building LLMs from scratch, but applications built on a platform and then trained from private user data and via user curation. If I implied otherwise, I wasn't clear. Sorry.

I assume Apple's LLMs are ethical. I also assume that Apple is exposing AI APIs for use by developers.

#LLM #Ibmz #AI #genAI #ethics #watsonx #ibm #Apple #intelligence #Writer #Author #Fiction #WritingCommunity #WritersOfMastodon #Programmer #Program #Application #Code #Coding

Cc: @vextaur

#llm #ibmz #ai #genai #ethics #watsonx

RS, Author, Novelist, Prosaist @[email protected] · 2025-01-06 · 20:22 UTC

AI [probably referring to a LLM] is not trained by professionals or a single end user, because it requires such huge amounts of input training data...

You are correct and you are incorrect.

From scratch finding data for pattern matching is tough and requires high performance engines, trade-offs, and money. But we stand on the backs of giants.

There are trained ethical LLMs, certified to be so and deep pockets to back the assertion and the necessary curation. They are not necessarily free. From those seeds AIs can be built to do the things of which I speak.

If IBM can do it (and they do; having gone to the training and hard sell, I know), Apple Intelligence could be built and use Apple engines as infrastructure. Big Blue's giant Z mainframes, which are blades in pretty artwork boxed server racks, are performant due to their custom chips, virtual system management, tuned I/O structure, and multitasking software. Apple chips are performant, custom, and cheaper for the end user. Apple Intelligence is likely Apple's WatsonX App-Killer that'll make the difference, and most certainly runs on Apple hardware increasingly running on renewables.

My point isn't so much building LLMs from scratch, but applications built on a platform and then trained from private user data and via user curation. If I implied otherwise, I wasn't clear. Sorry.

I assume Apple's LLMs are ethical. I also assume that Apple is exposing AI APIs for use by developers.

#LLM #Ibmz #AI #genAI #ethics #watsonx #ibm #Apple #intelligence #Writer #Author #Fiction #WritingCommunity #WritersOfMastodon #Programmer #Program #Application #Code #Coding

Cc: @vextaur

#boostingissharing #coding #code #application #program #programmer

RS, Author, Novelist, Prosaist @[email protected] · 2025-01-06 · 20:22 UTC

AI [probably referring to a LLM] is not trained by professionals or a single end user, because it requires such huge amounts of input training data...

You are correct and you are incorrect.

From scratch finding data for pattern matching is tough and requires high performance engines, trade-offs, and money. But we stand on the backs of giants.

There are trained ethical LLMs, certified to be so and deep pockets to back the assertion and the necessary curation. They are not necessarily free. From those seeds AIs can be built to do the things of which I speak.

If IBM can do it (and they do; having gone to the training and hard sell, I know), Apple Intelligence could be built and use Apple engines as infrastructure. Big Blue's giant Z mainframes, which are blades in pretty artwork boxed server racks, are performant due to their custom chips, virtual system management, tuned I/O structure, and multitasking software. Apple chips are performant, custom, and cheaper for the end user. Apple Intelligence is likely Apple's WatsonX App-Killer that'll make the difference, and most certainly runs on Apple hardware increasingly running on renewables.

My point isn't so much building LLMs from scratch, but applications built on a platform and then trained from private user data and via user curation. If I implied otherwise, I wasn't clear. Sorry.

I assume Apple's LLMs are ethical. I also assume that Apple is exposing AI APIs for use by developers.

https://habr.com/ru/companies/ruvds/articles/867316/

#LLM #Ibmz #AI #genAI #ethics #watsonx #ibm #Apple #intelligence #Writer #Author #Fiction #WritingCommunity #WritersOfMastodon #Programmer #Program #Application #Code #Coding

Cc: @vextaur

#llm #ibmz #ai #genai #ethics #watsonx

Habr @[email protected] · 2024-12-23 · 09:52 UTC

Второе пришествие мейнфреймов. Всё больше компаний хотят запускать ИИ у себя в офисе

Мейнфрейм IBM z16 во время лабораторных тестов в 2022 г, источник Приложения ИИ находят применение в бизнесе. Но есть проблема: корпоративные данные и документация представляют коммерческую тайну. Их нельзя передавать на сторону, тем более в облачную систему машинного обучения. Кроме того, что сама передача небезопасна, так ещё и публичная модель будет обучаться на наших секретах , а потом помогать конкурентам. В общем, у коммерческих компаний остаётся один вариант: поднимать собственный сервер или вычислительный кластер с ИИ. Таким образом, из эпохи облачных вычислений мы возвращаемся к старому доброму самохостингу, только сейчас это самохостинг GPU , серверы и мейнфреймы.

#IBM #мейнфреймы #Telum_II #AnythingLLM #ChatGPT #Meta #обман #человечество #Mount_Diablo #IBM_z16 #самохостинг #ЦОД #датацентр #WatsonX #Copilot #Twinny #llamafile #Ollama #GPT4All #FraudGPT #WormGPT #Khoj #LocalAI #ruvds_статьи

#ibm #мейнфреймы #telum_ii #anythingllm #chatgpt #meta

Habr @[email protected] · 2024-12-23 · 09:52 UTC

Второе пришествие мейнфреймов. Всё больше компаний хотят запускать ИИ у себя в офисе

Мейнфрейм IBM z16 во время лабораторных тестов в 2022 г, источник Приложения ИИ находят применение в бизнесе. Но есть проблема: корпоративные данные и документация представляют коммерческую тайну. Их нельзя передавать на сторону, тем более в облачную систему машинного обучения. Кроме того, что сама передача небезопасна, так ещё и публичная модель будет обучаться на наших секретах , а потом помогать конкурентам. В общем, у коммерческих компаний остаётся один вариант: поднимать собственный сервер или вычислительный кластер с ИИ. Таким образом, из эпохи облачных вычислений мы возвращаемся к старому доброму самохостингу, только сейчас это самохостинг GPU , серверы и мейнфреймы.

https://habr.com/ru/companies/ruvds/articles/867316/

#IBM #мейнфреймы #Telum_II #AnythingLLM #ChatGPT #Meta #обман #человечество #Mount_Diablo #IBM_z16 #самохостинг #ЦОД #датацентр #WatsonX #Copilot #Twinny #llamafile #Ollama #GPT4All #FraudGPT #WormGPT #Khoj #LocalAI #ruvds_статьи

#ibm #мейнфреймы #telum_ii #anythingllm #chatgpt #meta

Habr @[email protected] · 2024-12-23 · 09:52 UTC

Второе пришествие мейнфреймов. Всё больше компаний хотят запускать ИИ у себя в офисе

Мейнфрейм IBM z16 во время лабораторных тестов в 2022 г, источник Приложения ИИ находят применение в бизнесе. Но есть проблема: корпоративные данные и документация представляют коммерческую тайну. Их нельзя передавать на сторону, тем более в облачную систему машинного обучения. Кроме того, что сама передача небезопасна, так ещё и публичная модель будет обучаться на наших секретах , а потом помогать конкурентам. В общем, у коммерческих компаний остаётся один вариант: поднимать собственный сервер или вычислительный кластер с ИИ. Таким образом, из эпохи облачных вычислений мы возвращаемся к старому доброму самохостингу, только сейчас это самохостинг GPU , серверы и мейнфреймы.

https://habr.com/ru/companies/ruvds/articles/867316/

#IBM #мейнфреймы #Telum_II #AnythingLLM #ChatGPT #Meta #обман #человечество #Mount_Diablo #IBM_z16 #самохостинг #ЦОД #датацентр #WatsonX #Copilot #Twinny #llamafile #Ollama #GPT4All #FraudGPT #WormGPT #Khoj #LocalAI #ruvds_статьи

#ibm #мейнфреймы #telum_ii #anythingllm #chatgpt #meta

Habr @[email protected] · 2024-12-23 · 09:52 UTC

Второе пришествие мейнфреймов. Всё больше компаний хотят запускать ИИ у себя в офисе

Мейнфрейм IBM z16 во время лабораторных тестов в 2022 г, источник Приложения ИИ находят применение в бизнесе. Но есть проблема: корпоративные данные и документация представляют коммерческую тайну. Их нельзя передавать на сторону, тем более в облачную систему машинного обучения. Кроме того, что сама передача небезопасна, так ещё и публичная модель будет обучаться на наших секретах , а потом помогать конкурентам. В общем, у коммерческих компаний остаётся один вариант: поднимать собственный сервер или вычислительный кластер с ИИ. Таким образом, из эпохи облачных вычислений мы возвращаемся к старому доброму самохостингу, только сейчас это самохостинг GPU , серверы и мейнфреймы.

https://habr.com/ru/companies/ruvds/articles/867316/

#IBM #мейнфреймы #Telum_II #AnythingLLM #ChatGPT #Meta #обман #человечество #Mount_Diablo #IBM_z16 #самохостинг #ЦОД #датацентр #WatsonX #Copilot #Twinny #llamafile #Ollama #GPT4All #FraudGPT #WormGPT #Khoj #LocalAI #ruvds_статьи

#ruvds_статьи #localai #khoj #wormgpt #fraudgpt #gpt4all

michabbb @[email protected] · 2024-11-03 · 20:04 UTC

🔹 #IBM #Granite 3.0 introduces new family of #opensource #AI models, designed specifically for enterprise applications

🧠 New #LLM capabilities:
• Support for 12 languages and 116 programming languages
• Models ranging from sub-billion to 34B parameters
• Available under Apache 2.0 license
• Top performance in 15+ safety benchmarks

💻 Specialized versions include:
• #Granite for code: Focus on code generation & explanation
• #Granite for time series: Optimized for forecasting
• Granite Guardian: Enterprise data security & risk mitigation
• Geospatial model: Collaboration with #NASA for Earth observations

🛠️ Integration options:
• Available on #HuggingFace
• Deployable through #RedHat Enterprise Linux AI
• Compatible with #watsonx platform
• Supports tool-calling & RAG workflows

#ibm #granite #opensource #ai #llm #nasa

michabbb @[email protected] · 2024-11-03 · 20:04 UTC

🔹 #IBM #Granite 3.0 introduces new family of #opensource #AI models, designed specifically for enterprise applications

🧠 New #LLM capabilities:
• Support for 12 languages and 116 programming languages
• Models ranging from sub-billion to 34B parameters
• Available under Apache 2.0 license
• Top performance in 15+ safety benchmarks

💻 Specialized versions include:
• #Granite for code: Focus on code generation & explanation
• #Granite for time series: Optimized for forecasting
• Granite Guardian: Enterprise data security & risk mitigation
• Geospatial model: Collaboration with #NASA for Earth observations

🛠️ Integration options:
• Available on #HuggingFace
• Deployable through #RedHat Enterprise Linux AI
• Compatible with #watsonx platform
• Supports tool-calling & RAG workflows

#ibm #granite #opensource #ai #llm #nasa

michabbb @[email protected] · 2024-11-03 · 20:04 UTC

🔹 #IBM #Granite 3.0 introduces new family of #opensource #AI models, designed specifically for enterprise applications

🧠 New #LLM capabilities:
• Support for 12 languages and 116 programming languages
• Models ranging from sub-billion to 34B parameters
• Available under Apache 2.0 license
• Top performance in 15+ safety benchmarks

💻 Specialized versions include:
• #Granite for code: Focus on code generation & explanation
• #Granite for time series: Optimized for forecasting
• Granite Guardian: Enterprise data security & risk mitigation
• Geospatial model: Collaboration with #NASA for Earth observations

🛠️ Integration options:
• Available on #HuggingFace
• Deployable through #RedHat Enterprise Linux AI
• Compatible with #watsonx platform
• Supports tool-calling & RAG workflows

#ibm #granite #opensource #ai #llm #nasa

michabbb @[email protected] · 2024-11-03 · 20:04 UTC

🔹 #IBM #Granite 3.0 introduces new family of #opensource #AI models, designed specifically for enterprise applications

🧠 New #LLM capabilities:
• Support for 12 languages and 116 programming languages
• Models ranging from sub-billion to 34B parameters
• Available under Apache 2.0 license
• Top performance in 15+ safety benchmarks

💻 Specialized versions include:
• #Granite for code: Focus on code generation & explanation
• #Granite for time series: Optimized for forecasting
• Granite Guardian: Enterprise data security & risk mitigation
• Geospatial model: Collaboration with #NASA for Earth observations

🛠️ Integration options:
• Available on #HuggingFace
• Deployable through #RedHat Enterprise Linux AI
• Compatible with #watsonx platform
• Supports tool-calling & RAG workflows

#watsonx #redhat #huggingface #nasa #llm #ai

michabbb @[email protected] · 2024-11-03 · 20:04 UTC

🔹 #IBM #Granite 3.0 introduces new family of #opensource #AI models, designed specifically for enterprise applications

🧠 New #LLM capabilities:
• Support for 12 languages and 116 programming languages
• Models ranging from sub-billion to 34B parameters
• Available under Apache 2.0 license
• Top performance in 15+ safety benchmarks

💻 Specialized versions include:
• #Granite for code: Focus on code generation & explanation
• #Granite for time series: Optimized for forecasting
• Granite Guardian: Enterprise data security & risk mitigation
• Geospatial model: Collaboration with #NASA for Earth observations

🛠️ Integration options:
• Available on #HuggingFace
• Deployable through #RedHat Enterprise Linux AI
• Compatible with #watsonx platform
• Supports tool-calling & RAG workflows