It is well known among deep-learning manias that bilinear upsampling layers in TensorFlow have pixel-offset issues. But the problem remains to cause inconsistent computation flow when exporting a trained model in TensorFlow into another DL framework through various versions. In my case, a neural network model with bilinear upsampling layers showed weird behavior when converting the trained model from TensorFlow 2.5 to Apple Core ML by using coremltools 3.4. After uncountable coding, trials, and delete-delete-delete, I nearly gave up the consistent results of the upsampling layer between TensorFlow and Core ML. I wanted to use Keras in the latest TensorFlow 2.5 for training in Windows PC, and I wanted to use the previous coremltools 3.4 for converting the trained model to Core ML for my macOS laptop.
FORT MYERS, Fla – Many Southwest Floridians are still working from home, more than a year into the COVID-19 pandemic. A big question on many minds: Will we ever see a full return-to-work, and if so, when? Fox 4 spoke with CareerSource Southwest Florida to help answer those questions. CareerSource works with several local business owners to understand their hiring needs, so they have a good grasp on what most companies are doing. It said the short answer is yes, we will see a return-to-work for a majority of companies.
In a narrow glimpse of the increasingly automated future awaiting humanity, 10 silver robots shaped like ice-cream carts are delivering Southside Flying Pizza to hungry Austinites in Travis Heights and the Central Business District. The company behind the three-wheeled machines is hoping to grow its fleet exponentially and be part of a technological revolution in how people receive their deliveries. "Robots are your friends," said Luke Schneider, CEO of Michigan-based Refraction AI. "Robots are going to make your life more convenient. They're going to make your city more sustainable, and they're going to make your life better." The battery-powered devices, called REV-1s, go up to 15 mph and can recognize traffic lights and signs.
It's amazing how far we've come with the internet and IT in general. However, with technology come issues around cybersecurity. In response, Artificial intelligence (AI) is changing the face of cybersecurity. AI integrates the use of machine learning to identify characteristics of harmful software. This integration, when done well, has the promise to revolutionize the online market, especially in identity theft protection.
The never-ending fight with bias and AI systems that learn by watching YouTube. EU mobilizes to rein in tech giants. Facebook's AI has migrated all their AI systems to PyTorch. Within a year, there are more than 1,700 PyTorch-based inference models in full production at Facebook, and 93 percent of their new training models are on PyTorch. The times are hardly perfect for self-driving car companies.
The Techunting LinkedIn Robot is a valuable resource tasked with reducing work for business executives. This is a great opportunity that allows these people to focus on more valuable activities. In this article we will show you essential aspects about its creation and some tips for the pandemic era. If you want to know what this tool is about, uses and growth in markets, continue with us. Here we provide you with valuable information that can help you understand the reasons for its emergence and importance.
"My fascination with AI began when I first heard about IBM's supercomputer Deep Blue defeating Garry Kasparov." For this week's ML practitioner's series, Analytics India Magazine (AIM) got in touch with Hamsa Buvaraghan. Hamsa currently leads Google Cloud's Data Science and MLOps Solution team, building revolutionary software solutions for business problems using Google's Data Analytics and AI/ML products. She has an Engineering degree in Computer Science from Mysore University and an MBA, Honors from Saint Mary's College of California. Hamsa: My fascination with AI began when I was in India, back in 1997, when I heard about IBM's supercomputer Deep Blue defeating Garry Kasparov.
Since the list has gotten rather long, I have included an excerpt above; the full list is at the bottom of this post. At the entry level, the datasets used are small. Often, they easily fit into the main memory. If they don't already come pre-processed then it's only a few lines of code to apply such operations. Mainly you'll do so for the major domains Audio, Image, Time-series, and Text. Before diving into the large field of Deep Learning it's a good choice to study the basic techniques.
Every day, businesses and organizations are tasked with making more decisions than any human could ever hope to handle. Often, enterprises need to make complex business decisions with limited information on hand. With the help of AI-based products and AI-driven enterprise search solutions as a critical enabling technology, leaders can make better strategic and informed decisions by gaining insight from a vast amount of data in a short period. With the assistance of custom dashboards and 360-degree views of data, employees with different roles can each have a single view into all the information they need at its most appropriate level. The key message for companies is that making the right decisions and fast decisions are not either-or anymore.