Using artificial intelligence and machine learning in a product or database is traditionally difficult because it involves a lot of manual setup, specialized training, and a clear understanding of the various ML models and algorithms. You need to develop the right ML model for your data, train the model, evaluate it, optimize it, analyze it The post MindsDB: Automated Machine Learning with Jorge Torres appeared first on Software Engineering Daily.

Machine Learning – Software Engineering Daily

MindsDB: Automated Machine Learning with Jorge Torres

Creation Labs is helping bring Europe 1 step closer to fully autonomous long haul trucking. They have developed an AI Driver Assistance System (AIDAS) that retrofits to any commercial vehicle, starting with VW Crafters and MAN TGE trucks. Their system uses camera hardware mounted to the vehicle to capture video data that is processed with The post Creation Labs: Self Driving Trucks with Jakub Langr appeared first on Software Engineering Daily.

Creation Labs: Self Driving Trucks with Jakub Langr

Vectors are the foundational mathematical building blocks of Machine Learning. Machine Learning models must transform input data into vectors to perform their operations, creating what is known as a vector embedding. Since data is not stored in vector form, an ML application must perform significant work to transform data in different formats into a form The post Pinecone: Vector Database with Edo Liberty appeared first on Software Engineering Daily.

Pinecone: Vector Database with Edo Liberty

The incredible advances in machine learning research in recent years often take time to propagate out into usage in the field. One reason for this is that such “state-of-the-art” results for machine learning performance rely on the use of handwritten, idiosyncratic optimizations for specific hardware models or operating contexts. When developers are building ML-powered systems The post OctoML: Automated Deep Learning Engineering with Jason Knight and Luis Ceze appeared first on Software Engineering Daily.

OctoML: Automated Deep Learning Engineering with Jason Knight and Luis Ceze

Embedded Software Engineering is the practice of building software that controls embedded systems- that is, machines or devices other than standard computers. Embedded systems appear in a variety of applications, from small microcontrollers, to consumer electronics, to large-scale machines such as cars, airplanes, and machine tools.  iRobot is a consumer robotics company that applies embedded The post iRobot with Chris Svec appeared first on Software Engineering Daily.

iRobot with Chris Svec

Reinforcement learning is a paradigm in machine learning that uses incentives- or “reinforcement”- to drive learning. The learner is conceptualized as an intelligent agent working within a system of rewards and penalties in order to solve a novel problem. The agent is designed to maximize rewards while pursuing a solution by trial-and-error.  Programming a system The post Reinforcement Learning and Robotics with Nathan Lambert appeared first on Software Engineering Daily.

Reinforcement Learning and Robotics with Nathan Lambert

Companies can have a negative impact on the environment by outputting excess carbon. Many companies want to reduce their net carbon impact to zero, which can be done by investing in forests. Pachama is a marketplace for forest investments. Pachama uses satellites, imaging, machine learning, and other techniques to determine how much carbon is being The post Machine Learning Carbon Capture with Diego Saez-Gil appeared first on Software Engineering Daily.

Machine Learning Carbon Capture with Diego Saez-Gil

TensorFlow Lite is an open source deep learning framework for on-device inference. TensorFlow Lite was designed to improve the viability of machine learning applications on phones, sensors, and other IoT devices. Pete Warden works on TensorFlow Lite at Google and joins the show to talk about the world of machine learning applications and the necessary The post TensorFlow Lite with Pete Warden appeared first on Software Engineering Daily.

TensorFlow Lite with Pete Warden

Originally published July 30, 2019 “Internet of Things” is a term used to describe the increasing connectivity and intelligence of physical objects within our lives.  IoT has manifested within enterprises under the term “Industrial IoT,” as wireless connectivity and machine learning have started to improve devices such as centrifuges, conveyor belts, and factory robotics. In The post WebAssembly on IoT with Jonathan Beri (Repeat) appeared first on Software Engineering Daily.

WebAssembly on IoT with Jonathan Beri (Repeat)

Originally published April 17, 2019 Drishti is a company focused on improving manufacturing workflows using computer vision. A manufacturing environment consists of assembly lines. A line is composed of sequential stations along that manufacturing line. At each station on the assembly line, a worker performs an operation on the item that is being manufactured. This The post Drishti: Deep Learning for Manufacturing with Krish Chaudhury (Repeat) appeared first on Software Engineering Daily.

Drishti: Deep Learning for Manufacturing with Krish Chaudhury (Repeat)

Originally published June 21, 2019 Niantic is the company behind Pokemon Go, an augmented reality game where users walk around in the real world and catch Pokemon which appear on their screen. The idea for augmented reality has existed for a long time. But the technology to bring augmented reality to the mass market has The post Niantic Real World with Paul Franceus (Repeat) appeared first on Software Engineering Daily.

Niantic Real World with Paul Franceus (Repeat)

Originally published December 9, 2019 Machine learning algorithms have existed for decades. But in the last ten years, several advancements in software and hardware have caused dramatic growth in the viability of applications based on machine learning. Smartphones generate large quantities of data about how humans move through the world. Software-as-a-service companies generate data about The post Practical AI with Chris Benson (Repeat) appeared first on Software Engineering Daily.

Practical AI with Chris Benson (Repeat)

Originally published January 25, 2019 When TensorFlow came out of Google, the machine learning community converged around it. TensorFlow is a framework for building machine learning models, but the lifecycle of a machine learning model has a scope that is bigger than just creating a model. Machine learning developers also need to have a testing The post Kubeflow: TensorFlow on Kubernetes with David Aronchick (Repeat) appeared first on Software Engineering Daily.

Kubeflow: TensorFlow on Kubernetes with David Aronchick (Repeat)

Originally published April 3, 2017 A hedge fund is a collection of investors that make bets on the future. The “hedge” refers to the fact that the investors often try to diversify their strategies so that the direction of their bets are less correlated, and they can be successful in a variety of future scenarios. The post Hedge Fund Artificial Intelligence with Xander Dunn (Repeat) appeared first on Software Engineering Daily.

Hedge Fund Artificial Intelligence with Xander Dunn (Repeat)

For several years, we have had the ability to create artificially generated text articles. More recently, audio and video synthesis have been feasible for artificial intelligence. Rosebud is a company that creates animated virtual characters that can speak. Users can generate real or fictional presenters easily with Rosebud. Dzmitry Pletnikau is an engineer with Rosebud The post Rosebud: Artificially Generated Media with Dzmitry Pletnikau appeared first on Software Engineering Daily.

Rosebud: Artificially Generated Media with Dzmitry Pletnikau

Machine learning and data science episodes of Software Engineering Daily.