Baraban multiproduct cleaning technology V15
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The technology is new mechanical type of surface preparing, that imitating shot-blasting but don't using any abrasives. Therefore don't required additional equipment, protection, abrasives, special transportation. It's new, never used shock-pulse mechanics that calculated and practices founded by innovator. It's reliable, simple, efficient method for the fast and very cheap cleaning process in any industree.
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Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentationsLarge Language Model (LLM) and it’s Geospatial Applications
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UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Presentation of the OECD Artificial Intelligence Review of Germany
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TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
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Baraban multiproduct cleaning technology V15
- 1. «Baraban CT» LLC Gleb Druzhinin Devices for cleaning: Steels from rust, scale Sidewalks from ice crust
- 2. The problems of steel cleaning • Cleaning self costs $1-3 m²; o Generate dust; o Overhead transportation: waste abrasive equipment • Equipment prices: $6,000-10,000
- 3. Solution Video link Video link Video link • Instant seam cleaning • Local steel cleaning • Speed up to 20 m ²/h Mini Floor • Inline cleaning • Speed up to 35 m ²/h Automatic • Fast cleanup on a vertical and horizontal surfaces • Speed up to 65 m ²/h • Remote control • Cleaning self costs 1-3 $/m²; • Productivity - 20-50 m²/h; • Do not generate dust; • The cost of the devices from 1000$/pcs; • Compact-10-30 kg weight devices; • Not required: • Transportation; • Additional equipment; • Preparation and clean-up (before and after); • Overalls and remedies;
- 4. Ice crust removing problem • Pollution • from 100 g/m² • 0,3-0,5 €/kg • Speed 1-3 hours
- 5. Solution • Cleaning rate 60-100 m ²/h; • Does not damage the surface; • An environmentally friendly method; • Ability to remove thick layers of ice 1-3-5-10 > cm; Video link Video link
- 6. The markets Steel treatment. World markets • $77 blns • Ships repair, building; • Tube building; • Steel construction; • Cleaning services. Ice removing, Russia • ₽15 blns • Removal and cleaning; • Elimination of ice; • Purchase of equipment.
- 7. Business model Distribution Direct sales Wholesales Devices Cartridges Services Руб/м² Sales channels Service contracts Seasons Short term
- 8. Development strategy R&D Prototypes Pilots Fixing Service Promotion Testing&fixing First margin PR Advertising Government Manufacturing Self cost Production Supplies Sales Devices Cartridges Service
- 9. Team Gleb Druzhinin Artur Gurevich Konstantin Zharin CEO Head Engineer Design Engineer Total experience 10 years Sales, marketing, business development and business opening. 25 years R&D with 0, the start of production, standardization by ISO. 5 years R&D with 0, designing, prototyping.
- 10. Investing * Funding milestones 1. Venture project 1st quart – $80,000 • Office, equipment, samples, patenting, staff. 2nd quart – $150,000 • production, marketing, advertising. 3d quart – $100,000. • advertising operations. expenses 2. Joint venture* Joint research R&D complex Testings Pilot project Introduction of technology in enterprises partner Scaling and monetizing (International) or TOTAL: $320,000
- 11. Partner proposal Share in the company - 30%. Mln, USD 4 year 5 year Sales 5 7,8 Operating profit 1,7 2,8 The value of the company (by revenue) 3,4 5,6 Exit - sale to the industry leader:
- 12. Resume Prepared: Druzhinin Gleb. + 7-812-938-86-64 gleb@baraban.tech www.baraban.tech Diversified technology Strong competitive advantages International scale of business Successful project