June 28, 2018 | Written by: Kim Gregers Petersen
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You may think, that deep learning is mainly for nerds in universities and small start-up companies. Not true. Reality is that you will have a hard time finding any industry with no presence of companies doing Deep Learning activities. Admitted, in some market segments it is more common than in others, but no matter the industry it seems that the more successful companies tend to get much more value out of their data and their customers, and they use technologies like Machine Learning [ML], Deep Learning [DL] and eventually Artificial Intelligence [AI] to get to these advantages.
You are probably already on top of the definitions, but in short ML is about finding patterns in lots of data to be able to analyse data and eventually predict outcomes using models/tools like linear regression, decision tree, random forest and simple neural networks. Moving on to DL we use more complex, multi-layer neural networks, larger data sets and train DL-models to be able to deal with new, unknown data sets. If we put logics and action-oriented algorithms on top of the DL-trained systems, we end up having AI. IBM Watson is a perfect example of an AI eco-system. Right now, a lot of companies are putting resources in DL, and this short blog shows examples of European companies doing DL with IBM PowerAI running on IBM Power hardware.
WHAT IF you could use deep learning to investigate hours of VIDEO SURVEILLANCE footings to identify when truck drivers cheat and use the company card to fill up private cannisters with diesel? Diesel to be used at home, in private cars or sold on the side. With PowerAI Vision it is quite easy to train a DL-system to detect specific objects in images and video streams and raise a flag. And it GOES FAST, which is absolutely critical to the Danish end-user customer. Solution developed by an IBM Business Partner.
WHAT IF you are one of the largest FINANCIAL INSTITUTIONS, serving your customers with a multitude of services and now wants to offer Fraud Surveillance & Detection (in trading e-mail communication) as a PaaS-service? With a substantial background and knowledge in Monte Carlo Simulations and more traditional ML-tools, the company is now moving to DL to be able to offer even more – and more advanced – customer services. Due to the character of the services, the DL-environment really needs to be “enterprise grade”, putting IBM in the front seat due to IBMs knowledge of the needs of the financial industry combined with the ruggedness and full support of PowerAI and Power.
WHAT IF you are developing state-of-the-art TRUCKS and are involved in developing autonomous trucks as well as other related DL-work? You have a strategy to use open source software whenever possible and you want to have the fastest hardware available, since doing lots of training runs in the shortest possible time is CRITICAL. You value as well, that most of the PowerAI software stack is based on open source frameworks like TensorFlow and Caffe, assisted by unique IBM software and running on Power GPU-accelerated servers.
WHAT IF you are one of the largest FASHION retailers in the world and want to make sure, you are successful whenever you launch a new brand or a new fashion line, no matter where in the world your stores are located? Knowing customer behaviour coupled with market data got this European company starting using ML and DL years ago, but now moving from a traditional x86 platform to PowerAI on Power suddenly made DL applicable to a lot of new internal business use cases.
WHAT IF you are developing a VOICE-to-TEXT solution capable of not only doing the transcription of the whole dialogue during a financial meeting but on top of that analyse and draw conclusions and create a summary at the end of the meeting? Doing this live demands some powerful algorithms combined with vast amounts of [big] data and some very fast hardware, and this is exactly, what this Swedish company got with PowerAI and Power.
WHAT IF you are a Finnish UNIVERSITY with a special focus on HEALTH sciences, and you really need leading edge AI to the benefit of the students as well as the health sector? You need to be compliant with the Finnish HPC-center, run open source DL frameworks, and have api-access to Watson Health applications. You go for PowerAI running on Power with the newest and fastest NVIDIA Volta V100 GPU’s. You stay at the forefront of DL for health sciences.
You probably have your own “What If” questions. If not, you probably need someone to help you ask the questions. Trust me, if you have lots of data – and most companies have – deep learning might be the best and most easy way to extract value of your data. Feel free to contact me or my colleagues, if you need help to ask the What If questions.
Click here, to join my 20 minutes webinar on the same topic on August 23rd
For any further questions, do not hesitate to contact me at: KPeterse@dk.ibm.com