What's Next in AI: Fluid Intelligence (IBM Research Perspective)

Today’s AI is narrow. While many AI models deliver value in specific, well-defined situations, applying those same models to new challenges requires an immense amount of new data and training.

Enterprises need AI that is fluid and adaptable, capable of applying knowledge acquired for one purpose to new domains and challenges. They need AI that can combine different forms of knowledge, unpack causal relationships, and learn new things on its own.

In short, enterprises need AI with fluid intelligence — and that’s exactly what we’re building.

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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

The Impact Of IBM’s Move To Split On Its AI Initiatives

In one of the biggest news of the year, IBM recently announced that it is splitting its IT services business into a new company, temporarily named NewCo. The move headed by its CEO, Arvind Krishna, will lead to diversification of the world’s first big computing firm away from its legacy businesses to focus on high-margin cloud computing and AI business. The company believes that with this move, both the companies will be on an improved growth trajectory with more remarkable ability to partner and capture new opportunities.

With this, IBM becomes the big first computing firm to split up from its legacy business to focus on the new tech. The brand new IBM will accelerate and focus on the $1 trillion hybrid-cloud opportunity, whereas the NewCo. will focus on its services business with a revenue of around $19 billion. The NewCo will provide technical support to 4,600 clients in 115 countries, and is expected to record an expense of nearly $5 billion to be incurred in the separation and operational changes.

Krishna believes that this move will help the company revive growth after almost a decade of shrinking revenue, with a strategic focus on each of the businesses. “Now is the right time to create two market-leading companies focused on what they do best”, the company stated.

#opinions #ibm #ibm ai #ibm ai initiatives #ai

Artificial Intelligence: The Future of Modern Life Or a Cruel Deterrence?

Artificial Intelligence is now one of the most important emerging technologies to attempt to imitate human reasoning in AI networks. The benefits of Artificial Intelligent Software are tremendous and will revolutionize almost any industry. This technology is still in its early stages and there are many pros as well as cons of this technology. Although we cannot foresee the future, Artificial Intelligent software has the potential to significantly impact all industries and even society as a whole.
In the future, we are likely to see a vast improvement in AI technology and we will no longer need humans to operate those systems which make machines. We will also no longer need humans to program them. Nevertheless, the main question that remains is whether or not artificial intelligence is “good enough” and whether or not we are ready for that drastic change in our way of life. To date, we still have a long way to go and researchers are continuously making breakthroughs.

#ai #artificial intelligence #artificial intelligence (ai) #artificial intelligence and machine learning #ai algorithm #ai advantage

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