📣 If you work at an #enterprise you might want to read this blogpost.
💫 AI is advancing so fast that there is nowhere to hide from innovation anymore. Even the most conservative and slow-to-adopt enterprises are racing to understand and implement AI strategies. Jeanne Françoise Banky, MOSTLY AI's Customer Experience Manager, wrote a blogpost to help those looking to navigate enterprise AI successfully. Read Jeanne's blog here ➡ https://lnkd.in/dbRQxbbK
A great article about the practical use of AI in-house. Worth the read from managers to executives. Congrats Jeanne Françoise Banky, keep rocking!
💫 AI is advancing so fast that there is nowhere to hide from innovation anymore. Even the most conservative and slow-to-adopt enterprises are racing to understand and implement AI strategies. Jeanne Françoise Banky, MOSTLY AI's Customer Experience Manager, wrote a blogpost to help those looking to navigate enterprise AI successfully. Read Jeanne's blog here ➡ https://lnkd.in/dbRQxbbK
This article on why businesses are adopting private AI models is worth reading. I expect many enterprises will be headed down this path soon, if they’re not already! #aiadoption #genai #llm #datasecurity #servicelaunch
Industry is moving toward deploying custom private AI models in order to gain cost savings, increase security and build competitive advantage. It makes sense. Companies can reduce their up front investment by taking an existing publicly available model that someone else invested millions to train. Then add their business-specific data to the model, which is much less of a hurdle. This allows companies to leverage existing IP to gain competitive advantage while also maintaining control over it. Not to mention that this is also an opportunity to repurpose existing infrastructure. Let’s talk about how our expertise can benefit you in adopting AI. #ai #aiadoption #competitiveadvantage #llm #servicelaunch Check out this article for more of a deep dive on the reasons for deploying a private, secure LLM: https://lnkd.in/gUe6fKRv
A good Forbes article on Enterprise AI Governance In today's rapidly evolving digital landscape, Artificial Intelligence (AI) stands at the forefront of innovation, driving unprecedented changes across all sectors of society. However, with great power comes great responsibility. As we harness the capabilities of AI to solve complex problems, improve efficiency, and unlock new opportunities, the imperative for robust AI governance has never been more pronounced. Generative AI has added an additional layer of complexity as it leverages huge amount of unstructured and relatively ungoverned data.
CEO of TechUnity, Inc. , Artificial Intelligence, Machine Learning, Deep Learning, Data Science
By Zscaler, October 25, 2023. Enterprise use of AI tools will only grow, with industries like manufacturing leading the charge. Enterprises will secure AI/ML applications to stay ahead of risk. Enterprises will seek visibility and intelligent access controls around AI and ML applications. #genai #machinelearning #ai
🔐 Worried about proprietary data when experimenting with AI? The open source AI movement is paving the way for safer generative AI experiments while ensuring data control. Companies are leveraging these alternatives to maintain data stewardship and earn customer trust. Read more about the burgeoning open-source AI movement and its impact on responsible AI development. https://bit.ly/40YYIJD #AI #OpenSource
Industry is moving toward deploying custom private AI models in order to gain cost savings, increase security and build competitive advantage. It makes sense. Companies can reduce their up front investment by taking an existing publicly available model that someone else invested millions to train. Then add their business-specific data to the model, which is much less of a hurdle. This allows companies to leverage existing IP to gain competitive advantage while also maintaining control over it. Not to mention that this is also an opportunity to repurpose existing infrastructure. Let’s talk about how our expertise can benefit you in adopting AI. #ai #aiadoption #competitiveadvantage #llm #servicelaunch Check out this article for more of a deep dive on the reasons for deploying a private, secure LLM: https://lnkd.in/gUe6fKRv
Account Director - CORE Accounts | Broadcom Software Portfolio | Connecting Everything
We’ve entered the era of widespread adoption of generative AI tools. From IT to finance, marketing, engineering, and more, AI advances are causing enterprises to re-evaluate their traditional approaches to unlock the transformative potential of AI.
Balanced Perspective on Generative AI: 1. Enthusiasm with Realism: Embrace the potential of generative AI while keeping expectations aligned with organizational readiness and needs. Not all companies are prepared to fully harness this technology, so enthusiasm should be tempered with practicality. Assess readiness. 2. Generative AI as a Tool: Generative AI is a potent tool that enhances productivity and creativity. However, it should be regarded as just that—a tool. It complements human intelligence and expertise rather than substituting for them. Human judgment and creativity are indispensable for guiding and evaluating AI-generated outputs. Data Challenges in AI: 1. Data Quality and Relevance: Data quality happens to be a big pain point for many companies. Addressing data challenges is paramount. The data should be of high quality, error-free, and pertinent to the tasks we want generative AI to perform. Poor-quality or irrelevant data can lead to inaccurate and biased AI models. 2. Data Privacy and Compliance: Robust data privacy and security measures are necessary to safeguard sensitive information. Ensure compliance with data protection regulations, implement access controls, and use encryption to protect data. 3. Data Bias Mitigation: Identifying and mitigating biases in your data is critical to prevent biased outcomes in generative AI models. Implement strategies to promote fairness and prevent discriminatory results. Common Sense Matters: Finally, in all aspects of utilizing generative AI and managing data, relying on common sense as guiding principle is crucial. Sound judgment, critical thinking, and thoughtful decision-making are essential when navigating the complexities of AI technology and data management. #genai #artificialintelligence
A post on Generative #AI Framework developed by #IBM, fondly known as #watsonx https://lnkd.in/dCSvTN8b It discusses the nuances of Generative AI, its pros/cons from the perspective of ethics, accuracy & bias.
New AI innovation capabiliteis abound in Domino's fall 2023 release, as covered by DBTA! The update accelerates AI production and responsibility, making it easier for enterprises to innovate and scale AI projects with robust security. Dive into the details 👉 https://lnkd.in/gre7qEJP #AIInnovation #ResponsibleAI #DataScience 🔒💡
