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IBM Journey to AI blog
JANUARY 25, 2024
Adapting to the implications of increased AI adoption could include complying with complex regulatory requirements such as NIST , the EU AI Act , NYC 144 , US EEOC and The White House AI Act , which directly impact HR and organizational policies, as well as social, job skilling and collective bargaining labor agreements.
Unite.AI
APRIL 13, 2024
AI Adoption Among Marketers The winds of change are sweeping through marketing departments worldwide. A recent GetResponse survey revealed that 45% of respondents already use AI tools in their marketing strategies. Vague AI Regulations: The legal domains surrounding AI are still evolving.
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AI News
OCTOBER 24, 2024
The government’s commitment to supporting AI is evident through significant investments. In 2022, the UK government unveiled a National AI Strategy and Action Plan—committing over £1.3 Almost a third (31%) of SMEs have yet to adopt the cloud, and nearly half (47%) do not currently use AI tools or applications.
Unite.AI
NOVEMBER 21, 2024
This shift is also leading to new types of work in IT services, such as developing custom models, data engineering for AI needs and implementing responsible AI. The evolution of AI is promising but also brings many corporate challenges, especially around ethical considerations in how we implement it.
Unite.AI
OCTOBER 25, 2024
With these capabilities, the DA platform ensures that organizations can achieve faster, more accurate decision-making and optimize strategies for improved business outcomes. Can you elaborate on how the Quote AI tool improves quoting processes for businesses? GDPR, CCPA) and industry regulations (e.g.,
Towards AI
OCTOBER 18, 2024
Nvidia Quietly Launches AI Model that Outperforms GPT-4 Image by: Nvidia The Gist: Nvidia has released a new AI model, Llama-3.1-Nemotron-70B-Instruct, This launch marks a significant expansion of Nvidia’s AI strategy, shifting from hardware to high-performing AI software.
AWS Machine Learning Blog
MAY 9, 2024
Governance Establish governance that enables the organization to scale value delivery from AI/ML initiatives while managing risk, compliance, and security. Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI.
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