This series explores the accelerating digital strategies leaders are using to expand, integrate, and empower distribution channels to deliver greater value and better experiences to insureds while driving growth, efficiencies, and profits for insurers and their partners. Machine learning & AI are being used by digital leaders to help them increase distribution effectiveness by improving the insured experience, and to optimize channel management & processes. Join thought leaders as they discuss the strategies, results and lessons learned by those on the leading edge. One of InsurTech's top influencers, author, speaker and consultant in connected insurance, innovation, transformation and leadership. Insurance expert with 30 Yrs Sr. leadership experience in marketing, underwriting, claims, ops., reinsurance, analytics, & technology.

The Open Dynamic Robot Initiative Group is a collaboration between five robotics-oriented research groups, based in three countries, with the aim to build an Open Source robotics platform based around the torque-control method. Leveraging 3D printing, a few custom PCBs, and off-the-shelf parts, there is a low-barrier to entry and much lower cost compared to similar robots. The eagle-eyed will note that this is only a development platform, and all of the higher level control is off-machine, hosted by a separate PC. What's interesting here, is just how low-level the robot actually is. The motion hardware is purely a few BLDC motors driven by field-orientated control (FOC) driver units, a wireless controller and some batteries.

For many organizations, real-time data collection and data processing at scale can provide immense advantages for business and operational insights. The need for real-time data introduces technical challenges that require skilled expert experience to build custom integration for a successful real-time implementation. For customers looking to implement streaming real-time applications, our partner Confluent recently announced a new Databricks Connector for Confluent Cloud. This new fully-managed connector is designed specifically for the data lakehouse and provides a powerful solution to build and scale real-time applications such as application monitoring, internet of things (IoT), fraud detection, personalization and gaming leaderboards. Organizations can now use an integrated capability that streams legacy and cloud data from Confluent Cloud directly into the Databricks Lakehouse for business intelligence (BI), data analytics and machine learning use cases on a single platform.

We're Cruise, a self-driving service designed for the cities we love. We're building the world's most advanced, self-driving vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many. Cruisers have the opportunity to grow and develop while learning from leaders at the forefront of their fields. With a culture of internal mobility, there's an opportunity to thrive in a variety of disciplines.

About Apptegy Since our start in 2015, we've gone from a group of individuals to a community pushing toward the same goal of building a fantastic company with great people, great products, and most importantly, a great culture. To date, we have grown from a handful of school districts in Arkansas to thousands of school districts across the U.S. Apptegy is building products to empower school leaders to run better schools. We have the opportunity to help schools as they go through a radical shift in how they operate and to provide great technology to make that transition. Our Engineering team has grown significantly and so too has the number of schools and users. We look forward to meeting with you and telling you more about this opportunity to be part of a growing company, engineering organization, and to support a fast-scaling set of products.

Metaphysic, the company behind the Tom Cruise deepfakes, has raised $7.5 million. The London-based company develops artificial intelligence for hyperreal virtual experiences in the metaverse, the universe of virtual worlds that are all interconnected, like in novels such as Snow Crash and Ready Player One. The company raised the money from Section 32, 8VC, TO Ventures, Winklevoss Capital and Logan Paul. The funding will help expand Metaphysic's work on synthetic content creation tools for emergent metaverse worlds that are being built by Facebook and other networks. In addition to developing technology to scale hyperreal experiences in the metaverse, Metaphysic is aiming its synthetic media to connect influencers and their audiences in novel ways -- including via deepfake videos -- that are hyperrealistic, ethically created and uniquely compelling.

It turns out that artificial intelligence chatbots may be more like us than you'd think.

Today, the life sciences industry is at a critical inflection point. Its public profile has elevated due to its success at quickly developing vaccines to combat the COVID-19 pandemic. It has also built up a lot of trust. Despite the persistent issue of vaccine hesitancy, health -- including life sciences -- rose up in the rankings to become the second most trusted sector after technology, according to the 2021 Edelman Trust Barometer.[1] While the life sciences industry rightly has the approval and trust of its stakeholders -- including heath companies, insurers, clinicians and patients -- such approbation gives rise to an important challenge going forward.

Jakob Foerster an accredited Machine Learning Research Scientist who has been at the forefront of research on Multi-Agent Learning speaks with interviewer Kegan Strawn. Dr. Foerster explains why incorporating uncertainty into multi-agent interactions is essential to creating robust algorithms that can operate not only in games but in real-world applications. Jakob Foerster Jakob Foerster is an Associate Professor at the University of Oxford. His papers have gained prestigious awards at top machine learning conferences (ICML, AAAI) and have helped push deep multi-agent reinforcement learning to the forefront of AI research. Jakob previously worked at Facebook AI Research and received his Ph.D. from the University of Oxford under the supervision of Shimon Whiteson.

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