Bluevine is on a mission to enable a better financial future for small business owners through innovative banking solutions designed just for them. By combining best-in-class technology with advanced security and a deep understanding of the small business community, we deliver end-to-end banking and lending products that empower always-on entrepreneurs to grow their businesses with confidence. As a dynamic company with massive potential, we're backed by leading investors such as Lightspeed Venture Partners, Menlo Ventures, 83North, Citi Ventures, and nearly 9 years of proven success. Since launching in 2013, we have grown exponentially, amassing over 400,000 customers across all 50 states and a global team of more than 500 people. Our passion is driven by purpose: to give small businesses the tools they need to succeed and we're just getting started.

Genevieve Carlton holds a Ph.D. in history from Northwestern University. After earning her doctorate in early modern European history, Carlton worked as an assistant professor of history. Computer science majors work as software developers, security analysts, and web developers. But what if you want something a little different? The most badass jobs in computer science will push the field's boundaries and challenge you.

Data Scientists translate a massive amount of data collated by organizations to gain new insights, identify trends and find ways to streamline business practices. The growth of data is phenomenal, in 2020 alone, 50x more data will be generated than it did in 2011thus there is no surprise that the importance of Data scientists is gaining manifold over the years. It is the responsibility of a Data Scientist to make sense of this raw unstructured big data to analyze it and draw intelligent insights for strategic business decision formulations. What makes this job so unique is that data scientists require a very specific skill set which includes programming, coding, data management, statistics. Another indispensable skill set is Data Analytics, the art of converting intelligent insights from data sets.

Purpose: To investigate the feasibility of myelin water content quantification using fast dual-echo steady-state (DESS) scans and machine learning with kernels. Methods: We optimized combinations of steady-state (SS) scans for precisely estimating the fast-relaxing signal fraction ff of a two-compartment signal model, subject to a scan time constraint. We estimated ff from the optimized DESS acquisition using a recently developed method for rapid parameter estimation via regression with kernels (PERK). We compared DESS PERK ff estimates to conventional myelin water fraction (MWF) estimates from a longer multi-echo spin-echo (MESE) acquisition in simulation, in vivo, and ex vivo studies. Results: Simulations demonstrate that DESS PERK ff estimators and MESE MWF estimators achieve comparable error levels. In vivo and ex vivo experiments demonstrate that MESE MWF and DESS PERK ff estimates are quantitatively comparable measures of WM myelin water content. To our knowledge, these experiments are the first to demonstrate myelin water images from a SS acquisition that are quantitatively similar to conventional MESE MWF images. Conclusion: Combinations of fast DESS scans can be designed to enable precise ff estimation. PERK is well-suited for ff estimation. DESS PERK ff and MESE MWF estimates are quantitatively similar measures of WM myelin water content.

Amazon's hunt for a second headquarters, after several months of publicity stunts and dangled perks from cities and regions vying to lure the e-commerce giant, has been narrowed to 20 options from 238 bids. The company, which is based in Seattle, plans to invest $5 billion in development and create up to 50,000 jobs wherever it builds its newest hub. With the kind of enthusiasm normally reserved for bids to host the Olympics, governors, mayors, business leaders and others have pulled together proposals promoting the potential of their cities and regions, sometimes going to outlandish lengths. These are some of the places that caught Amazon's attention. Schools: The caliber of local schools is impressive, including Harvard University, Boston University, the Massachusetts Institute of Technology and Tufts University.

A mile away, at an Intelligentsia Coffee & Tea shop, a cup of coffee is delivered in less than 30 seconds, without any banter between barista and customer. The shop recently reintroduced large-batch coffee makers after shelving them years ago. The practice of making coffee by the cup--known as a pour-over--has been an essential skill for gourmet baristas for nearly a decade. The purposefully slow, personal nature of the ritual is an icon of the artisanal movement. Now, uttering words like "efficiency" and "consistency," some coffee shops are embracing the perks of machines.

This paper introduces a fast, general method for dictionary-free parameter estimation in quantitative magnetic resonance imaging (QMRI) via regression with kernels (PERK). PERK first uses prior distributions and the nonlinear MR signal model to simulate many parameter-measurement pairs. Inspired by machine learning, PERK then takes these parameter-measurement pairs as labeled training points and learns from them a nonlinear regression function using kernel functions and convex optimization. PERK admits a simple implementation as per-voxel nonlinear lifting of MRI measurements followed by linear minimum mean-squared error regression. We demonstrate PERK for $T_1,T_2$ estimation, a well-studied application where it is simple to compare PERK estimates against dictionary-based grid search estimates. Numerical simulations as well as single-slice phantom and in vivo experiments demonstrate that PERK and grid search produce comparable $T_1,T_2$ estimates in white and gray matter, but PERK is consistently at least $23\times$ faster. This acceleration factor will increase by several orders of magnitude for full-volume QMRI estimation problems involving more latent parameters per voxel.

Automated financial advice delivered by computer algorithm - often dubbed robo-advice - is a fast-growing business. But should you entrust your life savings to a computer? For many of us, talking about money is embarrassing - revealing our income and spending habits can feel like disrobing in public. So it's no wonder seeking investment advice from an impersonal, unbiased computer program is proving so popular. Consultancy firm Accenture found that 68% of global consumers would be happy to use robo-advice to plan for retirement, with many feeling it would be faster, cheaper, and more impartial than human advice.

Automation has become an incredibly hot topic in the tech world lately. It was the theme of the most popular items featured at the annual tech gadget conference, CES 2017, held earlier this month in Las Vegas. The show featured self-driving cars (which are also the main focus of all the biggest car shows in the country this year), robots, and Amazon's Echo, a voice assistant device that Amazon sold millions of during this past holiday season. More and more of our lives are becoming automated. In fact, most of my career coaching business is automated! Apps like Uber and Lyft make it possible to get a personal driver at your doorstep with the touch of a couple buttons.

Many are wondering on whether it is fitting to fear AI revolution or better yet know the perks of artificial intelligence with the utilization of VB Live. Also, it stands out that the era of Artificial Intelligence and its momentum has been affirmed by tech moguls such as Tesla's CEO, Elon Musk. Everything is shifting to a whole new level of technological advancements. At the middle of it all is the AI revolution. Ever since iPhones came equipped with the soothing tones of Siri, artificial intelligence entered the mainstream.