artificial intelligence

The Resistance to AI

It seems like every week; a technology vendor tells me how their AI product will free workers from mundane jobs and enable them to do more exciting work. And, every week I respond the same way (though sometimes more diplomatically) ‘that is not true.’ As AI works its way through blue-collar jobs, lower-paid white-collar jobs and now into higher-paid professions, that sales pitch that falls flat. In theory, AI automation could free workers from the mundane and create new and more exciting jobs. But in reality, that will seldom happen, workers are made redundant.

Research Agenda – 2019-20

Here is our research agenda for the coming year – it may change and will certainly be updated but hopefully this provides you some insight into what we are working on. As always if you have any suggestions or feedback reach out as we want to be sure our work is relevant, timely and of value!

Veritone: Illuminating AI

Recently we were contacted by Veritone to request an analyst briefing. At first I wasn’t sure that this was in the scope of our focus at Deep Analysis, but it turned out I was wrong. In short, Vertione is a publicly listed (NASDAQ – VERI) artificial intelligence vendor based in Southern California with roots in media and entertainment. Indeed it is still well known in that world, enabling media firms, studios, and sports organizations to analyze and monetize their digital assets.

DocAuthority: AI for Information Chaos

Finding value within mountains of unstructured data is both the challenge and the opportunity. Organizations have amassed millions, and in some instances billions, of files over the years. They pay heavily to store them as they believe that hidden in that mass of files are some of value. For sure there is value hidden within the mass, but there is also a high likelihood that there are files there that could cause organizational damage.

Salesforce Einstein a pragmatic approach to AI

The first thing to note is Salesforce is no longer trying to compete with IBM Watson. Rather than leading with AI as a broad solution, Salesforce has baked Einstein into its core offerings very tactically. Instead of touting complexity and power, Salesforce is delivering its AI, with easy to use interfaces and rather than requiring a specialist data scientist to set it up, Einstein can be configured by Salesforce administrators. In the same vein, the outputs of the 35 different AI modules that Einstein runs today are equally simple to digest and leverage. At Deep Analysis we like the approach of small tactical modules baked into service offerings that are easy to use.

ECM and Machine Learning – What are Box, IBM, OpenText and other Vendors doing?

To be fair, Artificial Intelligence and Machine Learning have been used for a long time in enterprise applications but their usage has really been for really complicated scenarios such as enterprise search (e.g., for for proximity, sounds etc) or sentiment analysis of social media content. But it has never been easy to use machine learning for relatively simpler use cases. Additionally, no vendor provided any SDKs or APIs using which you could use machine learning on your own for your specific use cases.