Conversational AI Firm Uniphore To Acquire Jacada

Uniphore, a Conversational AI company has agreed to acquire Jacada, a customer experience pioneer with the industry’s leading low code/no-code platform for contact centre automation.

https://analyticsindiamag.com/conversational-ai-firm-uniphore-to-acquire-no-code-platform-jacada/

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Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

This Week in AI | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai

This Week in AI - Issue #22 | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.Have fun!

Research Papers

• Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
• Slowing Down the Weight Norm Increase in Momentum-based Optimizers
• The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps
• AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
• Coherent Reconstruction of Multiple Humans from a Single Image
• Variational Bayesian Monte Carlo with Noisy Likelihoods
• GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning
• Are we done with ImageNet?
• How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds
• Background Modeling via Uncertainty Estimation for Weakly-supervised Action Localization
• The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps
• Image Deconvolution via Noise-Tolerant Self-Supervised Inversion
• Learning a Unified Sample Weighting Network for Object Detection

Articles

• Deepfake Detection Challenge Results: An open initiative to advance AI
• Slightly Unnerving AI Produces Human Faces Out of Totally Pixelated Photos
• NeoML Released as TensorFlow Alternative
• Google Meet takes on Zoom with AI-powered noise cancellation
• Open Compound Domain Adaptation
• Dense pose for animal classes with transfer learning
• 10 Ways Enterprises Are Getting Results From AI Strategies
• An understanding of AI’s limitations is starting to sink in
• Why we switched from Flask to FastAPI for production machine learning
• Simple Transformers
• The key differences between rule-based AI and machine learning
• Deep learning-based surrogate models outperform simulators and could hasten scientific discoveries
• HANDS-ON GUIDE TO OBJECT DETECTION USING YOLO
• Artificial neural networks that mimic the flexibility and computing power of the brain
• MIT researchers train AI to predict how humans paint works of art
• What Do Machine Learning Engineers Do Anyway?
• AI Is Amazing But Complicated, And We Don’t Necessarily Need To Plunge In Headfirst
• Deep learning networks track up to 100 animals simultaneously
• Is artificial intelligence changing art?

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai

Selecting a Conversational AI Platform

Businesses are quickly acknowledging the importance of Conversational AI (CAI) to increase their customer engagement and revenues. The question is no longer whether to deploy CAI, but rather which platform to use and how to leverage its capabilities.

In this series, Daniel Eriksson, Chief Innovation and Customer Success Officer at Artificial Solutions, gives insight on important aspects of a conversational AI platform that buyers often overlook. For example: what does language support really mean? What is localization? How do different deployment models impact the TCO? And maybe most importantly, how can the CAI platform not only help me during the first development sprints, but across the entire bot lifecycle?

Making Bot Developers More Productive

During the last six months, I’ve had a lot of conversations with companies (clients) and system integrators (partners) who have been building conversational bots. I’ve spoken with conversational bot developers, data linguistics reps, integration engineers, conversational designers, project managers, senior stakeholders, product owners, and many more.

At the same time, I’ve talked to existing, new, prospective, and former clients. These talks included people who had ambitious plans and succeeded and others who have had plans where they have struggled to generate impact.

Four Perspectives to Consider When Selecting your Conversational AI Platform

Select a Tool Your Development Team Can Grow With

See past the buzz-words like “awareness”, “understanding”, and “self-learning”.

Conversational AI is a fascinating space and still holds a lot of potential that is yet to be explored. Yet most companies who have experience of CAI tooling will tell you it’s all about engineering, and actually has a lot of resemblance to regular software or process flow development instead of being something ground-breaking new.

Sure, there are some terminologies both useful and specific for the space, like “intent recognition”, “entities”, and “context”. These words are related to the Natural Language Understanding (NLU) part of a conversational bot.

Find a Balance Between Pure Coding and Drag-and-Drop

Have you ever heard about low-code or no-code? In short, those concepts describe a user interface where a developer can configure or graphically design a process instead of having to write programming code. It is a great way to visualize how a program is executed and can be a quick way to build some things rapidly. Here comes the tricky part — for an effective Conversational AI solution with some ambition, you will still need to code. Your team will need to write code in some scripting language. If not, you will not be able to do the things you expect a bot to do. Do not shy away from this fact, as scripting and coding are super important to make a bot great. So, when you look at a toolset, evaluate it from the standpoint “how will the coding part work?”

Consider Possible Future Limitations

There is a lot of CAI tooling in the market today available to developers. Your job is to make sure that you don’t select tooling that is quick to build only the first MVP but also is useful for every new generation of your bot. When your ambitions grow, and your insights on how you can deliver a better bot user experience start to develop, you might realize that the tool you chose is holding you back.

#ai #artificial intelligence #natural language processing #conversational ai #ai platform #platform

Amsterdam And Helsinki Launch Open AI Registers

Amsterdam and Helsinki both launched an Open AI Register at the Next Generation Internet Summit. According to sources, these two cities are the first in the world that are aiming to be open and transparent about the use of algorithms and AI in the cities.

Currently, in the beta version, Algorithm Register is an overview of the artificial intelligence systems and algorithms used by the City of Amsterdam. The register is an effort to show where the cities are currently making use of AI and how the algorithms work.

Jan Vapaavuori, Mayor of Helsinki stated, “Helsinki aims to be the city in the world that best capitalises on digitalisation. Digitalisation is strongly associated with the utilisation of artificial intelligence. With the help of artificial intelligence, we can give people in the city better services available anywhere and at any time. In the front rank with the City of Amsterdam, we are proud to tell everyone openly what we use Artificial Intelligence for.”

#news #ai register #amsterdam ai #helsinki ai #open ai register #ai