TEAI Podcast ft. Jonathan Douglas, Head Actuary, Nayya
In this in-depth podcast conversation, Jonathan Douglas shares practical insights into how AI is being applied across the health ecosystem, what’s working, and what still needs fixing.
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TEAI Podcast ft. Andy Syrewicze, Microsoft Security MVP and Security Evangelist, Hornetsecurity
In this episode, Andy from Hornetsecurity breaks down how DMARC, SPF, and DKIM work together to protect organizations from phishing, spoofing, and email fraud.
TEAI Podcast ft. Naama Manova-Twito, co-founder & CEO, MarkeTeam.ai
Naama Manova-Twito joins the podcast to break down the AI revolution in the workplace, how to avoid AI ‘hallucination,’ and the urgent need to build culture around human/non-human hybrid teams.
How AI Analytics Quantify Human Creativity
A product design team is brainstorming ideas. Ideas abound, but creativity belongs to that class of slippery concepts: it is ill-defined and hard to pin down. Usually, the leaders get a feeling for which concepts hold promise, but often, can’t seem to articulate a reason why. They can’t quantify which ideas will connect most with…
How AI & Human Creativity Are Transforming Brand Storytelling
A customer watches a video of a certain brand on a social media platform and immediately receives a follow-up message on what they are lingering on. Later, the very same customer opens YouTube and sees a story continuation with the same brand voice, personalized. Collaboration is happening in the background, AI and Human Creativity working…
How Machines Inspire Human Creativity
Think of a designer working, looking for that spark to bring a new product concept alive. She opens a design tool powered by AI, generating fresh ideas she might never have considered. It’s a snapshot of how technology and imagination relate to evolution: machines aren’t just tools anymore, but collaborators extend the ability of humans…
How AI Labs Can Balance Speed, Cost, and Ethics
An AI Lab launches its next breakthrough model. Just as the final model begins to stabilize, a potential ethical risk is found within the training data. Pausing means delays and financial loss. Ignoring it risks regulatory fallout. This is the modern crossroads where every AI leader is forced to make a choice. The Modern AI…
Real-World Algorithms That Impact LLM Development
Imagine a self-driving car navigating and adapting to sudden changes in traffic. They utilize a network of algorithms that learn from real-world data. Similarly, LLM development (Large Language Model development) draws from real-world algorithms that shape how these systems understand, generate, and adapt to human language. From recommendation engines and neural networks to reinforcement learning…
How Evolution Strategies Slash LLM Training Costs
A startup building its own language model uses a large language model (LLM) to power its support platform. Cloud GPUs consume the budget, and optimization cycles drag on with limited returns. Tech giants are facing similar challenges when scaling or retraining large language models (LLMs). One approach to this problem is the use of evolutionary…