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Articles related to "process"


An Introduction to Machine Learning and AI in the Legal Industry

  • The most exciting aspect of applying AI in the legal profession lies in the automation of repetitive and straightforward tasks, like eDiscovery or judicial bill review, while enabling human experts to improve results beyond what machines or people could do alone.
  • As an example: A restaurant could, for example, better cater to their customers by building a machine learning model that analyzes their busiest periods, the most popular menu items, and estimated waiting times to more accurately schedule service staff and schedule stock supplies for improved customer experience.
  • When machine learning is implemented for legal operations, the data from invoices, matters, other legal records “trains” the AI to recognize patterns, while the expertise of the legal department staff provides feedback that allows the AI to improve results over time.
  • Through utilizing machine learning and AI, legal and claims departments see that compliance with their billing guidelines — an issue many companies struggle with — can be improved significantly across outside counsel relationships.

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Remastering Vintage Films with Temporal Source-Reference Attention Networks

  • In the paper DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement, the researchers show how their novel approach can bring new life to old films.
  • Although many recent studies have used recursive models for video processing, the researchers chose instead to use temporal convolutions to process video frames, as these can take account of information from multiple input video frames at once.
  • The researchers propose using source-reference attention as an attention mechanism, enabling the model to handle user-provided colour reference images.
  • The significant benefit of using source-reference attention-based networks is the model can use all the reference information when processing individual frames.
  • The researchers employed data creation and augmentation to train their model to not only perform colourization and noise removal, but also increase resolution and sharpness and improve contrast with temporal consistency.
  • The paper DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement is available on iizuka.

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Zhaoxin Unveiled Next-Generation x86 SoC Plans: 32-Core Servers, Sub-7nm Designs

  • In June this year, Zhaoxin introduced the company’s own 16-nanometer based Chinese homegrown x86 design, codename LuJiaZui. Two distinct families were introduced, the KaiXian KX-6000 series for client mobile and desktop computers, and the KaisHeng-30000 series for servers and networking devices.
  • Zhaoxin says it plans on quadrupling the number of cores in the new series – increasing the core count from eight to 32 cores per chip.
  • If Zhaoxin will be able to push the frequency further to as high as 3.5-4 GHz, they will close a good portion of the performance gap, but for their product to be at competitive levels with other x86 chips, in order to extract significant performance uplift from 7 and 5 nm, the company is going to step up its microarchitecture design.
  • At the SoC level, Zhaoxin plans PCIe Gen 4 and DDR5 memory support.

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Adidas innovation exec on recycling, future of shoes - Business Insider

  • The new model comes after the shoe first debuted in April and took seven years to perfect, according to Dharan Kirupanantham, senior manager of future technology innovation at Adidas.
  • Part of the challenge, Kirupanantham said, has been developing the technology and procurement processes necessary to not only manufacture such a shoe, but also to scale it effectively.
  • The second generation of Futurecraft continues the story and shows that we've actually been able to produce not just new products from old shoes, but also a high-performance running shoe.
  • So we don't necessarily try and be the experts in recycling, instead we worked with companies like BASF to identify recycling technology that enabled us to take shoes back and to shred and essentially re-pelletize them.

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Adidas innovation exec on recycling, future of shoes - Business Insider

  • The new model comes after the shoe first debuted in April and took seven years to perfect, according to Dharan Kirupanantham, senior manager of future technology innovation at Adidas.
  • Part of the challenge, Kirupanantham said, has been developing the technology and procurement processes necessary to not only manufacture such a shoe, but also to scale it effectively.
  • The second generation of Futurecraft continues the story and shows that we've actually been able to produce not just new products from old shoes, but also a high-performance running shoe.
  • So we don't necessarily try and be the experts in recycling, instead we worked with companies like BASF to identify recycling technology that enabled us to take shoes back and to shred and essentially re-pelletize them.

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Clustering: Software Engineering Roles on Github

  • To do so we employ data mining techniques for identifying different team roles and also assess the activities of team members within the software development and operations process.
  • The evaluation for the selection of the preferred parameters for each algorithm was done by repeatedly running each algorithm with different parameter values and compare the results based on each algorithm’s valuation metrics.
  • To answer each one of our questions specific metrics of the dataset were selected to determine the role classification and the contribution evaluation for every engineer.
  • Role classification was based on 4 metrics from the final dataset resulted after the pre-processing act (issues_participated, issues_opened, issues_closed, commits_authored).
  • Although the 3rd cluster also contains Low values considered the overall dataset but they are relatively higher than the 2nd cluster and that is why we can categorize it as Ops. In the other clusters, the same approach is followed as the first model in order to categorize them.

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An Introduction to Machine Learning and AI in the Legal Industry

  • The most exciting aspect of applying AI in the legal profession lies in the automation of repetitive and straightforward tasks, like eDiscovery or judicial bill review, while enabling human experts to improve results beyond what machines or people could do alone.
  • As an example: A restaurant could, for example, better cater to their customers by building a machine learning model that analyzes their busiest periods, the most popular menu items, and estimated waiting times to more accurately schedule service staff and schedule stock supplies for improved customer experience.
  • When machine learning is implemented for legal operations, the data from invoices, matters, other legal records “trains” the AI to recognize patterns, while the expertise of the legal department staff provides feedback that allows the AI to improve results over time.
  • Through utilizing machine learning and AI, legal and claims departments see that compliance with their billing guidelines — an issue many companies struggle with — can be improved significantly across outside counsel relationships.

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Lessons from Scrum

  • The longer the estimate, the greater the risk that you are underestimating the time required to complete this task.
  • If you find yourself attaching an estimate of more than two days, ask yourself: what is making this task more complex?
  • The biggest advantage we saw with acceptance tests was that requirements were discussed upfront with our stakeholders.
  • A by-product of having smaller tasks is that you tend to have smaller commits and conversely a shorter code review cycle.
  • Reducing the time pull requests stay in review keeps your cadence up, and reduces the risk of large changes being required for code review changes.
  • If you use a physical board for your tickets, think about how you can manage your digital assets in an orderly way.
  • It’s best to approach tasks that may look the most unpleasant or the most complex early on in the project.

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THE HEALTHCARE PAYMENTS REPORT: The strategies payments leaders are using to take advantage of the $3.7 trillion opportunity in US healthcare

  • Better-informed and more critical customers, along with a push to combat the complex and opaque medical billing process, are creating demand for innovation in the healthcare payments space.
  • Despite a titanic market size and room for innovation, digital transformation is occurring incrementally at best.
  • In fact, 90% of healthcare providers still leverage paper and manual processes for collections, according to data from a report commissioned by InstaMed and compiled by Qualtrics.
  • And even when healthcare providers offer digital solutions like online portals to customers (which 60% do), they seem to be falling short: While the majority of consumers claim they want to make appointments (68%), fill out registration forms (68%), and pay healthcare bills (61%) online, the share of consumers who actually do so hovers around 30% for those use cases.
  • Discrepancies like these make healthcare payments a greenfield for lucrative digital innovation.

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Adidas innovation exec on how the company created a fully recyclable sneaker over 7 years — and how it's thinking about the shoe of the future

  • The new model comes after the shoe first debuted in April and took seven years to perfect, according to Dharan Kirupanantham, senior manager of future technology innovation at Adidas.
  • Part of the challenge, Kirupanantham said, has been developing the technology and procurement processes necessary to not only manufacture such a shoe, but also to scale it effectively.
  • The second generation of Futurecraft continues the story and shows that we've actually been able to produce not just new products from old shoes, but also a high-performance running shoe.
  • So we don't necessarily try and be the experts in recycling, instead we worked with companies like BASF to identify recycling technology that enabled us to take shoes back and to shred and essentially re-pelletize them.

save | comments | report | share on