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Apple's head of machine learning quits after being made to come back to the office three days a week

Daily Mail - Science & tech

A senior director at Apple has quit his job in protest at the company demanding staff return to the office three days a week. Ian Goodfellow, the director of machine learning, is believed to be the most senior employee to resign so far as a result of the plan. On April 11, the company began mandating one day a week in the office - a requirement that rose to two days on May 2. By May 23, all staff had to be at their desks three days a week. A survey of Apple workers from April 13-19 found 67 percent saying they were dissatisfied with the return-to-office policy, Fortune reported. And Goodfellow, in his resignation note, said he would not do it.

How artificial intelligence helped save world trade


The effects of the Covid-19 pandemic continue to severely disrupt trade. Yet some trade finance banks had the foresight to plan for such an eventuality, utilising capabilities that overcome market-wide limits on documentary trade. As appetite for trade digitalisation grows, Conpend's CEO, Torben Sauer, explains how banks are increasingly turning to technology to automate their document checking using AI – eradicating logistical challenges following a surge in remote working caused by the pandemic, and streamlining paper-based processes and transforming operational efficiency Over the last two years, financial institutions (FIs) have experienced unparalleled disruption as the Covid-19 pandemic continues to impact regions across the world. What they have not experienced, however, is a major decline in functionality. While the crisis initially sent shockwaves through the financial markets in March 2020, the operations of most of the world's major banks converted to home working without a single day's loss in service.

If you want to make it big in tech, these are the skills you really need


Owen is a senior editor at ZDNet. Based in London, UK, Owen covers software development, IT workforce trends and the evolution of tech and work. As work and the workplace go digital, employees with technical know-how find themselves at a distinct advantage when it comes to moving their careers forward – regardless of what industry they work in. There are numerous factors at play here: the growth of automation, for example, means that machines and software are now able to replace routine, low-skilled tasks on factory floors and in the back office. The normalization of hybrid and remote working also means that the rules of work have changed, as have the tools and software employees interact with on a daily basis.

How enterprise device management platform, Radix, will revamp corporate training


We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. As organizations continue to migrate their workloads and shift to hybrid or remote work, cloud computing is growing at a rapid rate. Last week at the AWS Summit, according to Swami Sivasubramanian, the vice president of data, analytics and machine learning (ML) services at AWS, analysts project that between 5-15% of IT spend has moved to the cloud -- suggesting that organizations will continue to migrate even more of their workloads to the cloud in the future. The enterprise ecosystem is experiencing a disruption that's largely a result of more cloud-native applications coming to the scene. More companies are embracing a mix of both corporate devices and bring-your-own-device strategies.

Senior Data Scientist


As Google Cloud's premier partner in AI, Datatonic provides world-class businesses with cutting-edge data solutions in the cloud. We help clients take leading technology to the limits by combining our expertise in machine learning, data engineering, and analytics. With Google Cloud Platform as our foundation, we help businesses future-proof their solutions, deepen their understanding of consumers, increase competitive advantage and unlock operational efficiencies. Our team consists of experts in machine learning, data science, software engineering, mathematics, and design. We share a passion for data & analysis, operate at the cutting edge, and believe in a pragmatic approach to solving hard problems.

Remote Training and Virtual Mentoring for Hybrid and Remote Teams


Are you worried that having hybrid and especially full-time remote employees – even with remote training and virtual mentoring – will undermine junior employee on-the-job learning, integration into company culture, and intra and inter-team collaboration? This issue came up time and time again in my interviews with 47 mid-level and 14 senior leaders at 12 organizations I guided in developing and implementing their strategy for returning to the office and establishing permanent work arrangements for the future of work. If you enjoy video, here's a videocast based on this blog: And if you like audio, here's a podcast based on the blog These leaders acknowledged the reality that the future of work is mainly hybrid, with some staff full-time remote. After all, many high-quality surveys illustrate that 60-70% of all employees want a hybrid schedule permanently after the pandemic. Of the rest, 25-35% want a fully-remote schedule, and only 15-25% want full-time work in the office.

Artificial Intelligence


The Predict Vision AI platform will enable regular people to engage and participate in the new Artificial Intelligence-based future. Artificial Intelligence and other emerging technologies will take the global markets by storm. It will introduce, adapt, and retrain ordinary people, allowing you to grow and have an opportunity in a new leading-edge marketplace that will require a new, advanced workforce. A platform that will join A.I., Blockchain and Crypto at the same time, allowing ordinary people to enter both worlds and share wealth. We want to create a global AI ecosystem and community-based platform for knowledge sharing and collaborative learning and make AI accessible to everyone- empowering ordinary people to become extraordinary.

MLOps Engineer


As an MLOps Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce. You'll be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes. Whilst the position is a hands-on technical role, we'd be particularly interested to find candidates with a desire to lead projects and take an active role in leading client discussions. Your responsibilities will involve building trusted relationships with prospects, finding creative ways to use machine learning to solve problems, scoping projects, and overseeing the delivery of these engagements. To be successful, you will need an understanding of ML & Data Science fundamentals, as well as best software engineering practices such as automated testing and CI/CD.

The future of work: How everything changed and what's coming next


The future of work has dominated discussions both in the office and at home. What was previously'the great remote working experiment' has now morphed into'the great hybrid work pilot' and even'the great resignation' as companies shake up their workplace policies to align with a new, employee-led work landscape, and employees decide whether they like what they see. In the office, hybrid or remote, here's what is changing about where, when and how you do your job. According to a January 2022 Future Forum Pulse Survey of more than 10,700 knowledge workers, hybrid working – which combines remote working with days based in an office – has become the dominant model of work. The survey found that hybrid work arrangements increased 12 percentage points between May and November of 2021, rising from 46% to 58%.

AI/ML, Data Science Jobs #hiring


Medidata Solutions is an American technology company that develops and markets software as a service (SaaS) for clinical trials. These include protocol development, clinical site collaboration and management; randomization and trial supply management; capturing patient data through web forms, mobile health (mHealth) devices, laboratory reports, and imaging systems; quality monitor management; safety event capture; and monitoring.