Lao-dja Songdou Tchala

Data Scientist, Talan

Lao-dja Songdou Tchala is a Data-Scientist at Talan, a digital company that designs and executes enterprise business transformation for a wide range of international customers.In his role Lao is working with strategic partners on designing and setting methodologies and ML[AI]-based tools for improving traditional chatbots technologies. Prior joining Talan, as a Data-Scientist, he implemented projects in maintenance domain such as tools to measure the failure risk of industrial devices, predict the number of failures, and monitor their impact on photovoltaic power plants. As a data analyst engineer, he was involved in applying ML and Statistics to extracting trends and insights from power plants exploiting data. Lao Holds three master’s degree in Data-Science, Computer Science Systems’ Management and Computer Science Programming.

Past sessions

Summit 2021 From Chatbots to Augmented Conversational Assistants

May 27, 2021 11:00 AM PT

From Chatbots to Augmented Conversational Assistants: An Experimental Study combining AI and Crowdsourcing

Developing technology, including Natural Language Understanding and Machine Learning are taking Chatbots, Virtual Assistants, Conversational Bots... to an extent unheard of in the past. And yet, we cannot but notice that efforts are still needed for these interactive agents to attain a satisfactory level of conversational abilities. As a matter of fact, Bots still often cause a classic frustration effect when they reach limits in the scope of their powers.  

In order to take Bots beyond their technical boundaries:  

  1. We augmented them with technologies such as advanced data processing and Artificial Intelligence, including computer vision specific capabilities to mention just a few.
  2. We designed a unique approach based on crowdsourcing methods complementing and enhancing existing techniques to AI / Deep Learning.

In this talk, we will present the result of our research based on two tracks: 

  1. As part as our first iteration of research (aka “AVA”), we focused our efforts on identifying the most relevant AI/ML features that bring advanced conversational capabilities to Chatbots.  
  2. In a second iteration (aka “CIVA”), we concentrated our research on bringing more understanding and replying abilities to Bots defining a progressive methodology where data are improved. 

In this presentation you will see how we augmented Chatbots capabilities with: 

  1. Machine Learning 
  2. Computer vision
  3. Sentiment analysis
  4. Crowdsourcing
  5. Conversational methods
In this session watch:
Frederic Jacquet, Chief Innovation Officer, Talan
Lao-dja Songdou Tchala, Data Scientist, Talan