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Causal AI & LLM synergies: Enterprise decision making needs more than chatbots

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Events

Learn about the latest events and where we will be showcasing our latest developments.

QuantMinds – Why Causal AI Prevents Overfitting

The current state of the art in machine learning relies on past patterns and correlations to make predictions of the future.

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An Intro to Causal AI for Asset Management

causaLens' Ben Steiner will be speaking on Causal AI and its uses in asset management.

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AI in Finance Summit

A financial industry event to discover cutting-edge advancements in AI & Machine Learning and their adoption in financial services to increase efficiency & solve challenges.

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Actual causality, responsibility, explanations, and fairness – a bird’s eye view

causaLens' own Hana Chockler speaks on her leading research on actual causality, and its relationship to core concepts such as responsibility, explanation, and fairness.

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AI Humans Can Trust

Leaders who make the most transcendent decisions for our society are unable to trust current AI systems to help them make those decisions.

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BattleFin

With the market valued at over $1B currently and expected to continue growing at 40% yearly, the world of alternative data is changing rapidly.

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London AI Summit: Meet the scaleups shaping the future of AI

The AI Summit is the world's foremost event to look at the practical implications of AI for enterprise organizations: the actual solutions that are transforming business productivity.

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Quantitative Finance Conference – Why Causal AI Prevents Overfitting

The current state of the art in machine learning relies on past patterns and correlations to make predictions of the future.

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Advanced Alpha Testing Techniques

Our CEO Dr. Darko Matovski gives a presentation on Causal AI powered alpha testing techniques and participate in a panel with fellow industry leaders.

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Adapting ML strategies during a pandemic

The current state of the art in machine learning relies on past patterns and correlations to make predictions of the future. This approach can work in static environments and for closed problems with fixed rules.

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