Nancy Eke-Agu CAITL™,PMI-RMP®,PMP® on LinkedIn: #ai #innovation #searchtechnology #openai #searchgpt #digitalfuture… (2024)

In my latest article, I explore the implications of the newly implemented EU AI Act, which sets a standardized framework for AI governance throughout Europe. I analyze its impact on innovation, accountability, and the assurance of safe, transparent, and ethically aligned AI systems. Furthermore, I provide insights into what this means for end users and offer recommendations for other nations considering similar regulations to mitigate the risks associated with AI deployment. #AI #AIGovernance #AIRegulation #EthicalAI #TechPolicy #Innovation #EUAIAct #AICompliance #DigitalTransformation #NancyEkeAgu #ResponsibleAI

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I'm thrilled to share that I've been recognized as a Top Artificial Intelligence Voice on #LinkedIn! 😁 This acknowledgment fuels my passion for AI and reinforces my commitment to driving innovation and ethical practices in the field. Thank you to my incredible network for your support and engagement. Together, let's continue to explore, learn, and push the boundaries of AI!#TopVoice #AI #ArtificialIntelligence #Innovation #EthicalAI #TechLeadership #LinkedInTopVoice #AICommunity #TechInnovation

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The future landscape of AI will be shaped by three key elements: Proprietary data, Open models, and Bespoke interfaces.1. Proprietary DataThe value of AI hinges on high-quality data. Organizations that curate and maintain proprietary datasets will gain a significant competitive edge. Proprietary data ensures unique insights, tailored solutions, and superior performance. Companies investing in data collection, cleaning, and structuring will lead in AI innovation.2. Open ModelsOpen models democratize access to AI technology. By making models open-source, we foster collaboration, accelerate innovation, and lower entry barriers for smaller players. Open models ensure that a broader community can contribute to and benefit from AI advancements, driving the field forward more rapidly and inclusively.3. Bespoke InterfacesCustomization is key. Bespoke interfaces allow AI applications to be tailored to specific user needs and contexts. By designing interfaces that are intuitive and user-centric, we enhance the usability and adoption of AI technologies. Bespoke interfaces bridge the gap between complex AI systems and end-users, ensuring that AI tools are accessible and impactful.The synergy of proprietary data, open models, and bespoke interfaces will define the future of AI. Companies that strategically invest in these areas will be well-positioned to lead in the AI-driven world.#AI #MachineLearning #LLMs #DataScience #TechInnovation #OpenSource #UserExperience #AIModels #FutureOfAI #TechTrends #AItransformationLeader #NancyEkeAgu

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Large language models are rapidly growing in size and cost. For example according to The AI Index 2023 Annual Report, GPT-2, released in 2019, had 1.5 billion parameters and cost around $50,000USD to train. In comparison, PaLM, launched in 2022, boasts 540 billion parameters and cost about $8 million USD to train. PaLM is roughly 360 times larger and 160 times more expensive than GPT-2, highlighting the accelerating scale and investment in AI development. Interesting to take note of the figures- in parameters and costs, as we gradually progress toward SuperIntelligence. 🙂 #JustSaying #AI #MachineLearning #TechInnovation #LanguageModels #AIDevelopment #GPT2 #PaLM #AIEthics #TechTrends #AIResearch #NancyEkeAgu

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As AI systems increasingly influence crucial decisions in our lives, from loan approvals to healthcare, we must confront a critical challenge: How can we harness the power of probabilistic decision support models while preventing algorithmic discrimination?In this article, I explore the promise and perils of AI decision-making, diving into real-world cases of algorithmic bias and their far-reaching consequences. I also propose strategies for creating more equitable AI systems and call for a collaborative approach to this pressing issue in tech ethics.Join the conversation on building a more responsible AI future.#AIEthics #AlgorithmicBias #ResponsibleAI #TechPolicy #MachineLearning #DataScience #AIGovernance #InclusiveTech #FairnessInAI #EthicalML

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Embracing Explainable AI (XAI) is key to building trust and accountability in AI systems. By developing models that clearly explain their decisions, we can spot and address biases, ensuring fairer outcomes. This transparency not only boosts user confidence but also helps everyone understand how AI works, leading to more ethical and reliable applications.#AI #ExplainableAI #TechTransparency #ResponsibleAI #AIEthics #TechInnovation #AITrust #AIAccountability #DigitalTransformation #NancyEkeAgu

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"According to the Global Gender Gap Report of 2023, there are only 30 per cent women currently working in AI.If this trend persists, AI technologies and services will continue to miss out on diverse gender and racial perspectives. This disparity could lead to lower quality services and biased decisions in crucial areas like employment, credit, and healthcare. It's essential to address this gap to ensure more equitable and effective AI solutions. There is work to be done, and WE NEED MORE WOMEN!A good place to start is joining Women in AI so that together, we can do all we can towards closing the gender gap. #AI #GenderDiversity #TechEquality #AIethics #WomenInTech #BiasInAI #FutureOfWork #DiversityInAI

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