Unite.AI

SEPTEMBER 13, 2023

Increasingly though, large datasets and the muddled pathways by which AI models generate their outputs are obscuring the explainability that hospitals and healthcare providers require to trace and prevent potential inaccuracies. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

Explainability 278

Explainability Generative AI AI Tools AI 278

Unite.AI

MARCH 27, 2024

Likewise, ethical considerations, including bias in AI algorithms and transparency in decision-making, demand multifaceted solutions to ensure fairness and accountability. Addressing bias requires diversifying AI development teams, integrating ethics into algorithmic design, and promoting awareness of bias mitigation strategies.

Natural Language Processing 278

Natural Language Processing AI AI Automation 278

Unite.AI

SEPTEMBER 19, 2024

Use Cases Content Creation : Automating content production for marketing, technical documentation, or social media management. Conversational AI : Developing intelligent chatbots that can handle both customer service queries and more complex, domain-specific tasks.

LLM 246

LLM Automation Large Language Models OpenAI 246

AI Impacts

JULY 20, 2023

May) Current approaches to building general-purpose AI systems tend to produce systems with both beneficial and harmful capabilities. Further progress in AI development could lead to capabilities that pose extreme risks, such as offensive cyber capabilities or strong manipulation skills.

AI Strategy 100

AI Strategy Neural Network AI AI 100

Pickl AI

JANUARY 29, 2024

ML catalyses AI advancements, enabling systems to evolve and improve decision-making. AI automates and optimises Data Science workflows, expediting analysis for strategic decision-making. How does AI differ from Machine Learning? Data Science enhances ML accuracy through preprocessing and feature engineering expertise.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Unite.AI

NOVEMBER 28, 2024

This explains why discussing politics or societal issues often leads to disbelief when the other person’s perspective seems entirely different, shaped and reinforced by a stream of misinformation, propaganda, and falsehoods. C reative fields , long thought to be uniquely human domains, are now feeling the impact of AI automation.

Robotics 290

Robotics AI AI Algorithm 290

Unite.AI

JULY 25, 2024

This includes optimizing data collection processes, fostering transparency into AI decision making rationale, and leveraging AI model insights to refine human-driven processes. Explainability is key to fostering trust by providing clear rationale that lays bare the decision-making process.

AI 162

AI AI Automation Algorithm 162