Big Blue has taken a bite out of McDonald's, acquiring the burger chain's automated order taking (AOT) tech – and the "McD Tech Labs" that built it, for an undisclosed consideration that may or may not include an upsold serve of fries. The labs were created after Mickey Dee's 2019 acquisition of AI voice recognition startup Apprente – a deal touted as giving the burger-slinger the special sauce needed to build voice recognition tech into mobile ordering services or McKiosks. McDonald's told investors its efforts to cook Apprente's tech into something tasty have "shown substantial benefits to customers and restaurant crew experience". Once Big Blue bites into Big Mac's AI, McDonald's thinks the tech will really start to sizzle. "Moving forward, IBM's expertise in building customer care solutions with AI and natural language processing will help scale the AOT technology across markets and tackle integrations including additional languages, dialects and menu variations," reads the joint IBM/McDonald's McStatement.

Machine Reading Comprehension (MRC) is a relatively new part of natural language processing (NLP) and is an important part of AI that researchers around the world are working on. The MRC research community has been collaborating around several recently proposed datasets, e.g., the Stanford Question Answer Dataset (SQuAD) and the CNN/Daily Mail QA (CNN-DM) which was released by Google's DeepMind. The dataset generating the most activity in the research community since it was unveiled in 2016 is SQuAD. If you are not familiar with SQuAD, according to their website it is the "reading comprehension dataset, consisting of questions posed by crowd workers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage." One of the features of SQuAD is that they maintain a leaderboard where we can track the rapid progress that is being made in MRC and see how our latest models are doing relative to the state of the art.

When it comes to enterprise customer care, machine learning enables virtual assistant solutions to automate tasks that used to require a live agent: password resets, address and complex information collection, even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. With the growing challenges and volume of customer interactions that most companies must handle, that flexibility, efficiency, and accuracy is exactly what's needed. By incorporating natural language processing, many of today's automated customer care solutions can more accurately understand what callers are saying.

When it comes to enterprise customer care, machine learning enables virtual assistant solutions to automate tasks that used to require a live agent: password resets, address and complex information collection, even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take enterprise customer care to the next level. Of course, success comes with a cost.

When it comes to enterprise customer care, machine learning enables virtual assistant solutions to automate tasks that used to require a live agent: password resets, address and complex information collection, even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take enterprise customer care to the next level.

When it comes to enterprise customer care, machine learning enables Virtual Assistant solutions to automate tasks that used to require a live agent: password resets; address and complex information collection; even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies' must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take enterprise customer care to the next level.

When it comes to enterprise-level customer care, machine learning enables Virtual Assistant solutions to automate tasks that used to require a live agent: password resets; address and complex information collection; even sales support. Integrating machine learning into customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies' must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take customer care to the next level.