Opinions

The Future Of Robotics Is Fuzzy

Robotics using fuzzy logic will be a game-changer for flexible robotic production.

Kai-Fu-Lee, AI, AI Risks, AI dangers

Former Google Exec Lists 4 Dangers Associated With AI

Former Google exec Kai-Fu Lee lists the top four risks associated with the use of AI.

Facebook AI Model

Facebook’s First AI Model Based On Audio

A lower temperature causes repetitive sentences, while a medium temperature makes sentences locally coherent.

China Fintech

The Unfortunate Tale of China’s FinTech Companies

They don’t face most financial regulations and are free from supervision.

Amazon algorithms

Amazon’s Use Of Algorithms To Increase Employees’ Productivity: Fair Or Not?

Amazon deploys data, surveillance and algorithms to accelerate the productivity of its warehouse workers. But how ethical is it?

Will AI And The Lightning Network Set A Future Trend?

Startups in India will be significantly impacted by AI and Lightning Networks.

Does ModelOps Represent A New Horizon For MLOps?

One of the most important concerns with AI adoption today is ModelOps solutions.

Knowledge-Based Systems & How APIs Can Drive Their Adoption?

The new initiatives in knowledge-based systems will revolutionise the decision-making process.

Met Gala, AI

How AI Is Used In Met Gala Over The Years

Here’s a cumulative list of how and when technology made it to the red carpet at the Met Gala in the last couple of years.

Spatio-Temporal Transformer Network: Can Text Detection Be Achieved Through It?

Spatio-Temporal Transformer Network (STTN) and contemporary techniques are combined in STRIVE (Scene Text Replacement In VidEos).

Why ML Needs To Move On From The Bias-Variance Tradeoff Narrative

Is it time to bid farewell to bias-variance tradeoff when it comes to machine learning?

Hugging Face Launches Optimum, An Open Source Optimisation Toolkit For Transformers At Scale

Hugging Face Launches Optimum, An Open Source Optimisation Toolkit For Transformers At Scale

We will soon announce new hardware partners who have joined us on our journey toward machine learning efficiency.