This exemplifies progress with responsibility in AI. At IBM, we are proud of and committed to pushing the envelope on what it means to be transparent when it comes to creating our Granite foundation models! #ibm #ibmgranite #ibmresearch
Nirmit Desai’s Post
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AI LLMs are measured on a number of benchmarks including performance, size, availability...and transparency. When trust in data is key, kudos to @ibm #Granite. IBM beats Meta, OpenAI in Stanford transparency index https://avoa.co/3UTxcuv #CIO #LLM #AI #GenAI #Data
IBM beats Meta, OpenAI in Stanford transparency index
ciodive.com
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watsonx SME and AI Technical Specialist at IBM | ⚡️Data Nerd Josh⚡️ | Podcast Host 🎙 |My mission is to help clients solve their most critical Data and AI challenges while also creating engaging content.
Do you know everything that went into building and training the large language modules that you use? Can your organization trust it? Either IBM, it’s a no brainer. #largelanguagemodel #llm #ibm #meta #openai
"IBM beats Meta, OpenAI in Stanford transparency index" 💥 https://lnkd.in/d5cV_yS7. While a single AI model won't rule them all, it's important to remember how we need to have trust and transparency in the AI models we work with. How else can we ensure reliable outcomes? #watsonx
IBM beats Meta, OpenAI in Stanford transparency index
ciodive.com
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Always better to start with transparency then try and add it later.. Watsonx an entire suite to help guide your AI journey
"IBM beats Meta, OpenAI in Stanford transparency index" 💥 https://lnkd.in/d5cV_yS7. While a single AI model won't rule them all, it's important to remember how we need to have trust and transparency in the AI models we work with. How else can we ensure reliable outcomes? #watsonx
IBM beats Meta, OpenAI in Stanford transparency index
ciodive.com
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As IBM's Account Technical Director for State of California, I orchestrate IBM's technology teams and help our clients embrace IBM's open Hybrid Cloud and AI platforms | IBM Distinguished Engineer | Field CTO
As the demand for generative AI is expected to grow this year, it becomes imperative for the public sector to embrace responsible use of this technology. Only by doing so can governments establish themselves as trustworthy stewards. Read more about IBM's principles in this blog post by our Global Government industry leaders. #2024 #generativeAI #publicsector
5 key areas for governments to responsibly deploy generative AI - IBM Blog
https://www.ibm.com/blog
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We at IBM aim to be the primary provider of enterprise AI solutions, providing essential tools, data layer, governance and data fabric for constructing necessary workflows for your business operations. A great article Patrick Moorhead ! #IBM #AIStrategy #ArtificialIntelligence #AIforbusiness #datamanagement #AI #dataanalytics
A Year In Review Of IBM’s Ambitious AI Strategy
forbes.com
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IBM Vice President, Managing Director, Financial Services, Advocate and Mentor for Women in IT
IBM's WatsonX AI and data platform offers a comprehensive suite of tools for AI development and deployment. WatsonX utilizes Generative AI, machine learning, deep learning, and foundation models to support a broad range of functions, from data science to supply chain optimization. The platform's AI studio, data lakehouse, and governance capabilities ensure trust, accountability, and transparency in all AI processes and projects. With its flexibility and automation capabilities, WatsonX can reduce costs and cycle times by over 50%, making it a game-changer for businesses across industries. #IBM #AI #DataScience #Automation Great article - worth the read: https://lnkd.in/ek2_BgJw
A Year In Review Of IBM’s Ambitious AI Strategy
forbes.com
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Two favorite bits from this filing: 1) We got to use the phrase "epistemic humility" 2) This portion on what we think a productive path forward would be for regulators interested in addressing AI safety risks: "Novel regulatory approaches may be warranted at some point to address potential risks of foundation models, but the consequences of an imprecise approach to regulation are too great to risk untested solutions. As NIST works to develop the scientific understanding of identifying and evaluating AI safety risks, an NTIA-led pilot that works with NIST to test and iterate on regulatory responses to novel risks not already addressed by existing regulatory frameworks would be extremely beneficial. Another regulatory model worth exploring as part of this sandbox approach is creating a toolbox of regulatory solutions that could be leveraged if and when certain milestones in the science of AI safety evaluations are achieved. This “conditional regulation” approach should focus on domains of AI that many believe to be intrinsically higher risk, such as bioengineering. While it is intuitive that an AI model capable of generating novel molecular structures for pharmaceutical research might be able to also design dangerous biological agents, there are no widely-agreed upon, standardized processes for empirically detecting this capability in a model, nor evaluating whether access to such a model could increase marginal societal risk of harm. As NIST’s AI Safety Institute develops these processes and evaluations, NTIA could propose relevant regulatory agencies work with the Institute to co-develop and test regulatory interventions precisely targeted to mitigate such risks that would only go into effect after this scientifically-grounded understanding is established."
AI Ethics, Data Privacy & Cybersecurity | General Counsel | Corporate Secretary & Board Advisor | Government Relations | Identifying & mitigating risk for multinational technology companies
At IBM, we believe that an open innovation ecosystem for #AI is critical to ensuring the benefits of AI are distributed broadly throughout society, and that development coexists with safety. That’s why we responded to the request for comment on open-weight AI models from the National Telecommunications and Information Administration (NTIA) at the U.S. Department of Commerce. In our comments to the administration, we shared our support for open innovation and a democratized AI ecosystem. We commend the NTIA for seeking comments from across industries as it works to address challenges and questions around AI governance and what it looks like in practice. Trustworthy AI is everyone’s responsibility, and here at IBM, we strongly believe that policymakers should regulate AI at the point of risk, and where the technology touches people’s lives. You can read IBM’s comments in full, and learn more about why we support open innovation for AI, below: https://lnkd.in/e8RHmWcq.
IBM's Response to NTIA’s Request for Comment on Dual Use Foundation Artificial Intelligence Models with Widely Available Model Weights - IBM Policy
ibm.com
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VP & CTO for AI, Governance and Data for SW Dev @ IBM | PhD, watsonx, AI Governance, Automation, AI Ethics, Responsible AI, Enteprise AI
Careful balance... read more on IBM's response to the NTIA's request. Responsible AI requires careful consideration at the point of use, risk at time of use is an absolute requirement~!!! Please take a read and share your thoughts. #responsibleAI #AIEthics #EthicalDebt #sustainableAI #enterpriseAI
AI Ethics, Data Privacy & Cybersecurity | General Counsel | Corporate Secretary & Board Advisor | Government Relations | Identifying & mitigating risk for multinational technology companies
At IBM, we believe that an open innovation ecosystem for #AI is critical to ensuring the benefits of AI are distributed broadly throughout society, and that development coexists with safety. That’s why we responded to the request for comment on open-weight AI models from the National Telecommunications and Information Administration (NTIA) at the U.S. Department of Commerce. In our comments to the administration, we shared our support for open innovation and a democratized AI ecosystem. We commend the NTIA for seeking comments from across industries as it works to address challenges and questions around AI governance and what it looks like in practice. Trustworthy AI is everyone’s responsibility, and here at IBM, we strongly believe that policymakers should regulate AI at the point of risk, and where the technology touches people’s lives. You can read IBM’s comments in full, and learn more about why we support open innovation for AI, below: https://lnkd.in/e8RHmWcq.
IBM's Response to NTIA’s Request for Comment on Dual Use Foundation Artificial Intelligence Models with Widely Available Model Weights - IBM Policy
ibm.com
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Here's our current IBM take on why it's important to help protect an open innovation ecosystem for #AI.
AI Ethics, Data Privacy & Cybersecurity | General Counsel | Corporate Secretary & Board Advisor | Government Relations | Identifying & mitigating risk for multinational technology companies
At IBM, we believe that an open innovation ecosystem for #AI is critical to ensuring the benefits of AI are distributed broadly throughout society, and that development coexists with safety. That’s why we responded to the request for comment on open-weight AI models from the National Telecommunications and Information Administration (NTIA) at the U.S. Department of Commerce. In our comments to the administration, we shared our support for open innovation and a democratized AI ecosystem. We commend the NTIA for seeking comments from across industries as it works to address challenges and questions around AI governance and what it looks like in practice. Trustworthy AI is everyone’s responsibility, and here at IBM, we strongly believe that policymakers should regulate AI at the point of risk, and where the technology touches people’s lives. You can read IBM’s comments in full, and learn more about why we support open innovation for AI, below: https://lnkd.in/e8RHmWcq.
IBM's Response to NTIA’s Request for Comment on Dual Use Foundation Artificial Intelligence Models with Widely Available Model Weights - IBM Policy
ibm.com
