How Bitvore Builds AI One Step at a Time

There’s a common perception that to work correctly, AI must process vast reams of data. Indeed, there’s no denying that AI developed in this way can get a lot done—but the problem is that this method [...]

Running Up Against the Limits of Common Sense in Artificial Intelligence

One problem in artificial intelligence is a tendency to run out of training data. There are occasional instances in which there is not enough training data to train an AI model fully. In [...]

Bitvore Data Case Study: Electric Vehicles in Reverse Due to Chip Shortage

Why is there a Global Semiconductor Shortage?

With the onset of the pandemic, carmakers like General Motors, Ford Motor and Volkswagen were forced to temporarily shut down production lines. [...]

Applying Security Principles to AI Production

AI is becoming more common—which of course means that bad people are going to try and attack it. It’s a tale as old as time, but are AI companies doing enough to protect themselves and their products?

AI Stumbles Without Good Data, Despite Advances in Techniques

Data is important to AI—and probably more important than you think. Data scientists and developers like to tout their AI techniques and models, but there's no such thing as a model that doesn't fall [...]

The Future of Artificial Intelligence: 3 Predictions

The COVID-19 pandemic has underscored the need for flexibility, rewarding those companies most adept at adjusting to changing conditions. With the end of the pandemic on the horizon, businesses are [...]

How AI Can Lead to Better Environmental, Social and Corporate Governance Investing

Wealth managers have a lot of data at their fingertip these days. They can precisely tailor investments to their investors' appetite for risk, using AI financial tools to gauge the business climate [...]

AI Makes Its Way into the Venture Capital Community

Investing in startups is always a risk - for every Tesla, you get about 50 Segways. It’s not ideal. The limits of human intuition mean that identifying the next big thing is neither easy nor [...]

Why Machine Learning Projects Fail

 

Software development is a mature field, built on decades of experience. Organizations have sophisticated methodologies for developing, testing, debugging, and putting apps into production as stable [...]