The Equal Employment Opportunity Commission issued updated guidance stating that federal laws don’t prevent an employer from requiring workers to be vaccinated.
However, in some circumstances, federal laws may require the employer to provide reasonable accommodations for employees who, because of a disability or a religious belief, aren’t vaccinated. For example, the EEOC said as a reasonable accommodation, an unvaccinated employee entering the workplace might wear a face mask, work at a social distance or be given the opportunity to telework.
The new guidelines also say that federal laws don’t prevent or limit incentives that can be offered to workers to voluntarily take the vaccine. And employers that are administering vaccines to their employees may also offer incentives, as long as the incentives aren’t coercive.
The directive, issued as one of Mr. Biden’s first actions after taking office, could require employers to develop mandates on masks, physical distancing and air ventilation. The Centers for Disease Control and Prevention currently provides guidelines on these measures, but they aren’t mandatory.
Labor Secretary Marty Walsh “reviewed the materials, and determined that they should be updated to reflect the latest scientific analysis of the state of the disease,” a Labor Department spokeswoman said. “He has ordered a rapid update based on CDC analysis and the latest information regarding the state of vaccinations and the variants. He believes this is the best way to proceed.”
Machine learning (ML) is one of the most transformative technologies we will encounter in our generation. Whether enhancing customer experiences and boosting employee productivity or cutting costs and reducing fraud, ML is helping organizations tackle their biggest challenges and opportunities.
As the Vice President of ML at AWS, I talk to business leaders a lot about how ML can help them. What I hear from them often is that they want to take advantage of it, but they don’t have the ML expertise necessary to turn data into insights.
So, over the last few years, we’ve developed services that have pre-trained ML models, “intelligence,” built right into them. Many of these services are based on the same technology used on Amazon.com. And best of all, they can be added to applications and processes without any ML experience required.
These solutions help automate manual tasks that challenge specific industry verticals, like content curation in media and entertainment (M&E) companies, visual inspections in manufacturing, and text and insight extraction from paperwork in healthcare and financial services organizations.
&E organizations use ML to personalize content recommendations, increase user engagement, reduce customer churn, review content for compliance and brand safety, and much more. With ready-made intelligence solutions, more of them are realizing these benefits sooner and building market advantage without having to build ML expertise themselves.
For example a library of more than 55,000 episodes that appeals to a broad base of customer audiences. They wanted to help customers find curated content that matched their specific interests, so they implemented Amazon Personalize.
household name in Sweden, manufacturing a broad assortment of foods. One of their most popular brands is Billy's Pan Pizza, a microwaveable pizza baked and packed at a speed of two pizzas per second. Their machine vision system used for quality assurance couldn’t detect defects on new product types that include multiple toppings.
Healthcare organizations are also applying ML to make improvements, such as to personalize and prioritize patient care, increase the accuracy of diagnoses, and speednatural language processing service that uses ML to extract relevant medical information from unstructured textOver the past few years, ML has come a long way. The barriers to entry have been significantly lowered, enabling more industries to quickly apply ML to their most pressing challenges and biggest opportunities. And it’s only the beginning. We’re committed to creating solutions that help all organizations harness the power of ML.
Over the past few years, ML has come a long way. The barriers to entry have been significantly lowered, enabling more industries to quickly apply ML to their most pressing challenges and biggest opportunities. And it’s only the beginning. We’re committed to creating solutions that help all organizations harness the power of ML.
I let her pick the due date, but each month it rolls around, she begs to wait for one more pay period, because her account is empty. She begs to reduce the amount owed, and complains about the portion of her income.
Each month I move the date back a week, to the point where she’s really only contributing 9 to 10 months out of the year. She’s never able to pay the full $560, and she completely fails to understand that the percentage of income for me is identical, and that I am making the exact same contributions in comparison to our household.
Additionally, I deposit $155 after tax directly into her checking account from my paycheck. So she’s really just giving me my own money back. In April, there were three pay periods, where I deposited $465 into her checking account. She begged to contribute $500 late,
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