Oliver King-Smith, CEO and founder smartR AI

Picture of Oliver King-Smith, CEO and founder smartR AI
Oliver King-Smith is CEO of smartR AI, a company which a company which facilitates and empowers organizations to extract real value from their data in an ethical, responsible, and sustainable manner using cutting edge AI technology.
Beyond the Hype: Unleashing the Power of Private, Affordable, Assistive AI for a Better Future

Beyond the Hype: Unleashing the Power of Private, Affordable, Assistive AI for a Better Future

Tech News & Insight
AI stirs both excitement and concern. While some companies rush to take advantage of it, many are cautious due to the challenges and costs. However, there may be a better approach: using Assistive Intelligence with small, specialized models instead of Large Language Models. This method is more affordable and can benefit businesses and society. Emphasizing open-source technology respects privacy and fosters true innovation. By focusing on solving real problems, we enable growth and empower people to explore Assistive AI without high costs.
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Rethinking AI: From Artificial to Assistive Intelligence

Rethinking AI: From Artificial to Assistive Intelligence

Tech News & Insight
This article reflects on the misconceptions we have about AI, and discusses the fallacy of understanding AI’s underlying mechanisms, as it can demonstrate intelligent behavior despite our understanding. AI is developing its own form, capable of analyzing vast datasets, identifying patterns, and making connections that humans might take years to discover. And highlighting the power of partnership in AI projects, where both human and machine intelligence contribute their unique strengths. By combining human strengths with AI’s, we can create something greater than the sum of its parts.
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The Evolution of AI Training Efficiency: Emerging Trends and Market Implications

The Evolution of AI Training Efficiency: Emerging Trends and Market Implications

Tech News & Insight
Recent advancements in artificial intelligence training methodologies are challenging traditional assumptions about computational requirements and efficiency. Researchers have discovered an “Occam’s Razor” characteristic in neural network training, where models favor simpler solutions over complex ones, leading to superior generalization capabilities. This trend towards efficient training is expected to democratize AI development, reduce environmental impact, and lead to market restructuring, with a shift from hardware to software focus. The emergence of efficient training patterns and distributed training approaches is likely to have significant implications for companies like NVIDIA, which could face valuation adjustments despite strong fundamentals.
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Challenging the Notion That LLMs Can’t Reason: A Case Study with Einstein’s Puzzle

Challenging the Notion That LLMs Can’t Reason: A Case Study with Einstein’s Puzzle

Tech News & Insight
When Apple declared that LLMs can’t reason, they forgot one crucial detail: a hammer isn’t meant to turn screws. In our groundbreaking study of Einstein’s classic logic puzzle, we discovered something fascinating. While language models initially stumbled with pure reasoning – making amusing claims like “Plumbers don’t drive Porsches” – they excelled at an unexpected task.
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Enhancing Behavioral Intelligence AI Decision Engines with SLMs: Use Cases Across Industries

Enhancing Behavioral Intelligence AI Decision Engines with SLMs: Use Cases Across Industries

Tech News & Insight
The article discusses the potential of Small, Specialized, and Symbolic Learning Machines (SLMs) in Behavioral Intelligence (BI) Artificial Intelligence (AI) decision engines. Unlike traditional machine learning models, SLMs use symbolic reasoning to make decisions and provide clear explanations for their predictions. This transparency is crucial in sensitive areas where decision-making explanations are essential. The article explores various applications of SLMs in BI AI decision engines and concludes that SLMs offer a promising pathway towards more energy-efficient and sustainable AI, reducing computational demands and enabling edge deployment while providing comparable performance for specific tasks.
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Data, energy, people and planet: Some SLM balance in the polarized digital age

Data, energy, people and planet: Some SLM balance in the polarized digital age

Tech News & Insight
SLMs present an exciting opportunity for creating a more energy-efficient and sustainable approach to AI. They lower computational requirements, facilitate edge deployment, and maintain similar performance levels for certain tasks, which can help lessen the environmental footprint of AI while still providing essential advantages. Additionally, prioritizing data privacy and responsible data management can greatly reduce energy use in data centers. By encouraging ethical data practices, empowering users, and promoting energy efficiency through SLMs, we can pave the way for a greener and more privacy-aware digital landscape.
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From Visionary to Victory: How to Successfully Implement AI in Your Organization

From Visionary to Victory: How to Successfully Implement AI in Your Organization

Tech News & Insight
AI can drive innovation, efficiency, and competitive advantage in organizations. However, implementing AI projects can be challenging, especially when endpoints are unclear and outcomes are uncertain. To effectively apply AI, focus on tasks that humans find tedious or complex, well-defined information environments, and opportunities to capture critical knowledge. Overcoming common challenges in AI project implementation includes focusing on measurable outputs, iterating and refining AI systems, and distinguishing between bugs and limitations in AI architecture. Maximizing the value of AI in an organization involves enhancing human capabilities, focusing on how AI can make employees more effective and efficient. By implementing these strategies, organizations can maximize the value of their AI investments and drive innovation, efficiency, and competitive advantage.
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AI’s Reality Check: When the Hype Train Hits a Brick Wall

AI’s Reality Check: When the Hype Train Hits a Brick Wall

Article & Insights
AI projects are struggling to deliver expected benefits due to complexity, cost, time, technical challenges, and market dynamics. The innovation-adoption gap is outstripping the market’s ability to adapt and find practical applications, leading to overinvestment in promising ideas without sufficient market demand. A fundamental shift in perspective is needed: AI should be viewed as a tool to enhance human productivity, not as a replacement for humans. Successful AI projects incorporate humans at critical junctures, such as problem definition, data preparation, model training, output validation, and ethical oversight. Balancing potential with pragmatism is crucial for successful AI implementation.
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AI and Sports: Game-changer?

AI and Sports: Game-changer?

Article & Insights
Sports, an activity defined by human movement, may not appear to have much to do with AI. But if there is one thing we know about the impact of AI, is that it is pervasive. Certainly, the sports industry will be no exception. With the Olympics just finalized in Paris, we are here to guide you through how AI seeks to improve the sports industry, along with some of the risks we should be aware of going forward.
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Unlock Hidden Relationships in Your Data with SCOTi’s new Graph Creator Function

Unlock Hidden Relationships in Your Data with SCOTi’s new Graph Creator Function

News
At the request of ex government minsters, smartR AI has developed SCOTi Graph Creator, the latest addition to the SCOTi® AI suite. Graph Creator allows organizations to trace complex relationships in unstructured data and transform those relationships into actionable insights, while maintaining control over sensitive information.
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EU AI Act: A Game-Changer with Some Head-Scratchers

My Take on the EU AI Act: A Game-Changer with Some Head-Scratchers

News
The European Union AI Act, a 458-page document with 113 articles, aims to categorize AI systems based on risk levels: unacceptable, high, limited, and minimal risk. It bans government social scoring systems and manipulative AI systems, with strict compliance requirements for high-risk areas like infrastructure and healthcare. As the AI field continues to evolve rapidly, the legislation will need to keep pace with updates and interpretations. It’s essential for companies to prioritize transparency and risk assessment in their AI development process to comply with the new requirements. The EU AI Act represents a significant step in regulating AI, and its impact on the industry will be closely monitored as it unfolds.
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DEMYSTIFYING GDPR AND AI - SAFEGUARDING PERSONAL DATA IN THE AGE OF LARGE LANGUAGE MODELS

GDPR and AI: Safeguarding Personal Data with LLMs

Article & Insights
Can you safely input personal data into AI models? The answer: it depends.

When it comes to using personal information in cutting-edge AI technology like LLMs, it’s important to consider GDPR compliance and the potential risks associated with data retention and leaks. The article delves into the key considerations, looks into mitigating risks as well as LLM’s and GDPR compliance.
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Smaller, Faster, Greener: Cutting-Edge AI Models Do More with Less

Article & Insights
The demand for electricity and water to power and cool AI servers is ever increasing. Researchers are developing innovative solutions to mitigate the environmental impact. Four promising techniques include model reuse, ReLora, MoE, and quantization. As AI becomes more prevalent, we need to proactively reduce energy and water usage to benefit clients and contribute to a sustainable future.
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smartR AI Unveils SCOTi - Scotland's Powerful, Private, and Most Loyal AI Assistant

smartR AI Unveils SCOTi – Scotland’s Powerful, Private, and Most Loyal AI Assistant

News
Scottish based smartR AI™ has launched its wee dynamo that makes you smarter inside. SCOTi™ AI is a totally private and secure GPT agent, a trusty companion that helps organizations increase efficiency. Every SCOTi is trained to solve your unique business case and is owned by the client for added privacy and security.
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Doomsday Data Drought: Data Scientist Shortage Gets Worse as GenerativeAI Supercharges Data

Doomsday Data Drought: Data Scientist Shortage Gets Worse as GenerativeAI Supercharges Data

Article & Insights
Data Scientists are already in short supply. One of the most promising areas to make Data Scientist more productive is Generative AI. However, while Generative AI will increase the productivity of Data Scientists, it will lead to an even more serve crunch in the Data Scientist supply.
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Private 5G/LTE and CBRS Networks in Action: Transforming Industries

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AI-Powered Service Assurance – Leveraging DPUs, GPUs, and GenAI for Next-Gen Networks

AI-Powered Service Assurance – Leveraging DPUs, GPUs, and GenAI for Next-Gen Networks

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5G NR Transparent NTN: Deployment Aspect and Challenges

5G NR Transparent NTN: Deployment Aspect and Challenges

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This article explores the deployment of 5G NR Transparent Non-Terrestrial Networks (NTNs), detailing the architecture's advantages and challenges. It highlights how this "bent-pipe" NTN approach integrates ground-based gNodeB components with NGSO satellite constellations to expand global connectivity. Key challenges like moving beam management, interference mitigation, and latency are discussed, underscoring...

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