Karla is on a mission to reshape the frustrating post-purchase experience by making e-commerce delivery simple and enjoyable for consumers, online shops and carriers. Tedious post-purchase experiences, such as insufficient transparency, inaccurate delivery times and complex product returns, negatively impact customers' online shopping journey. The Karla team envisions a future without a frustrating post-purchase experience in online-shopping. Our solution enables merchants, carriers and consumers to communicate throughout the entire post-purchase process - all in one simple application.No stress. No mess. All your deliveries where you want them. Consumers get an intuitive overview of all deliveries, can easily manage them and adjust individual delivery details.The experience will go beyond the delivery and unboxing moment all the way through returns, refunds, claims, questions and potential repurchases in future to elevate today’s online shopping experiences. Our product will be launched later this year. However, you are welcome to sign up at gokarla.io to be one of the first to experience HAPPY DELIVERIES.

Karla

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A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Conclusion

The Geeks of War: How Dzyga's Paw Innovated Ukraine's Drone Operations

The immediate trigger for this blog is the less-than-expected performance by India’s ruling party of the last decade, i.e., BJP and what transpired afterward in the media, on social media, & various WhatsApp groups. What one got to see was hysteria & then crazy speculation about why it happened and what were the root causes. Nearly 1000 reasons must have been thrown around. Something similar happened during Covid. From the laymen to the experts to the heads of state, everyone had some solution or other every day. Often, a contradictory solution to what they suggested just a few days back. In both cases, & through multiple other experiences, I have come to realize that… People are very poor at finding out the root cause(s) of a problem. When presented with a problem, coming up with a solution, implementing the solution, & ensuring that it is sustainable is part of what I do, day in and day out. Having done this for several years, across several industries, & with several organizations. I reached the same conclusion as above. Be it a technical problem like a memory leak, a behavioral issue, problems in the process, etc. It does not matter what the nature of the problem is. When I look back, I can see some recurring issues. “Correlation does not mean causation” is an idea most people struggle with. Just because event B happens when event A also happens, just because when you increase input x, output y increases, they automatically jump to establish a cause-and-effect relationship. When multiple variables affect an outcome, two contradictory aspects need to be considered simultaneously. We need to isolate the impact of each variable. Also, we need to understand their combined impact & sometimes the interrelations between the variables themselves. What happens is that one of the variables is identified (sometimes, just correlation, sometimes causation). It gets fine-tuned, & we announce victory only to realize that the improvements we thought would materialize haven’t. Then there is the problem of complex vs complicated. Almost all techniques we are aware of are suitable for solving complicated problems. These techniques involve reductionist approaches which fail miserably in solving complex problems. One of the greatest assets for a problem solver is humility. “I don’t know” is a very powerful statement when you are trying to solve a problem. It means that you are open to challenge/validate every assumption. While you might have tonnes of experience, you are ready to take a fresh look at the problem at hand. The customers/stakeholders though like to only hire people who can show a high degree of confidence and claim that “I know the solution”, “ This is nothing new for me”, “I have already solved it” or “Here ..I have a panacea..don't think JUST DO IT”. Another challenge is often people who pay an analyst/problem solver want immediate actions. They are not ready to accept that problem-solving needs time .. time to observe, time to analyze, time to hypothesize, time to run experiments, & time to see the outcomes of a change. Yes sounds like someone is going to sit on his butt for long periods but the more complex a problem, the more time you need to sit on your butt doing all these things rather than being “Action Jackson.” When I ask for time to observe/collect data, I am told “That is already done, here is the data”. There is very little appreciation of the fact that data that is gathered by a 3rd party while it is a good starting point for a problem solver, going through the process of capturing this data in itself is a learning experience & provides a lot of insights. It also avoids biases that the data-capturing machinery might have. Last but not least, the urge to declare victory prematurely. This happens the most in large corporates as their timing is everything. Just before the quarter ends, just before the appraisal cycle, one needs to show the results. So, the moment green shoots of progress are seen, out goes the email with 20 people, 200 in CC. Then there is a long chain  of “Kudos,” “Amazing Work,” etc.. till one discovers that the victory was short-lived. The concept of letting the changes “BAKE IN”, wait & watch are alien. To conclude, here are things to keep in mind. Correlation does not mean causation. When multiple variables affect an outcome, individuals, as well as combined impact, need to be understood. Complex & Complicated systems need very different problem-solving approaches. “I don’t know” is a very good starting point. If this person has solved problems in the past, he will solve your present problem as well; even if his current status is “I don’t know.” Problem-solving is a lot of brain work. Don’t get biased by the lack of visible action. The success of the solution depends on how well data collection happens. Don’t short-circuit it. It takes time to provide long-term/permanent solutions for problems. Don’t be like Bart & Lisa with your non-stop “Are we there already?” Having identified the problems, the actual process of implementing the solutions has its own set of issues. But that is for some other day to write about. Credit: Photo by Karla Hernandez on Unsplash The immediate trigger for this blog is the less-than-expected performance by India’s ruling party of the last decade, i.e., BJP and what transpired afterward in the media, on social media, & various WhatsApp groups. What one got to see was hysteria & then crazy speculation about why it happened and what were the root causes. Nearly 1000 reasons must have been thrown around. Something similar happened during Covid. From the laymen to the experts to the heads of state, everyone had some solution or other every day. Often, a contradictory solution to what they suggested just a few days back. In both cases, & through multiple other experiences, I have come to realize that… People are very poor at finding out the root cause(s) of a problem. When presented with a problem, coming up with a solution, implementing the solution, & ensuring that it is sustainable is part of what I do, day in and day out. Having done this for several years, across several industries, & with several organizations. I reached the same conclusion as above. Be it a technical problem like a memory leak, a behavioral issue, problems in the process, etc. It does not matter what the nature of the problem is. When I look back, I can see some recurring issues. “Correlation does not mean causation” is an idea most people struggle with. Just because event B happens when event A also happens, just because when you increase input x, output y increases, they automatically jump to establish a cause-and-effect relationship. When multiple variables affect an outcome, two contradictory aspects need to be considered simultaneously. We need to isolate the impact of each variable. Also, we need to understand their combined impact & sometimes the interrelations between the variables themselves. What happens is that one of the variables is identified (sometimes, just correlation, sometimes causation). It gets fine-tuned, & we announce victory only to realize that the improvements we thought would materialize haven’t. Then there is the problem of complex vs complicated. Almost all techniques we are aware of are suitable for solving complicated problems. These techniques involve reductionist approaches which fail miserably in solving complex problems. One of the greatest assets for a problem solver is humility. “I don’t know” is a very powerful statement when you are trying to solve a problem. It means that you are open to challenge/validate every assumption. While you might have tonnes of experience, you are ready to take a fresh look at the problem at hand. The customers/stakeholders though like to only hire people who can show a high degree of confidence and claim that “I know the solution”, “ This is nothing new for me”, “I have already solved it” or “Here ..I have a panacea..don't think JUST DO IT”. Another challenge is often people who pay an analyst/problem solver want immediate actions. They are not ready to accept that problem-solving needs time .. time to observe, time to analyze, time to hypothesize, time to run experiments, & time to see the outcomes of a change. Yes sounds like someone is going to sit on his butt for long periods but the more complex a problem, the more time you need to sit on your butt doing all these things rather than being “Action Jackson.” When I ask for time to observe/collect data, I am told “That is already done, here is the data”. There is very little appreciation of the fact that data that is gathered by a 3rd party while it is a good starting point for a problem solver, going through the process of capturing this data in itself is a learning experience & provides a lot of insights. It also avoids biases that the data-capturing machinery might have. Last but not least, the urge to declare victory prematurely. This happens the most in large corporates as their timing is everything. Just before the quarter ends, just before the appraisal cycle, one needs to show the results. So, the moment green shoots of progress are seen, out goes the email with 20 people, 200 in CC. Then there is a long chain  of “Kudos,” “Amazing Work,” etc.. till one discovers that the victory was short-lived. The concept of letting the changes “BAKE IN”, wait & watch are alien. To conclude, here are things to keep in mind. Correlation does not mean causation. Correlation does not mean causation. When multiple variables affect an outcome, individuals, as well as combined impact, need to be understood. When multiple variables affect an outcome, individuals, as well as combined impact, need to be understood. Complex & Complicated systems need very different problem-solving approaches. Complex & Complicated systems need very different problem-solving approaches. “I don’t know” is a very good starting point. If this person has solved problems in the past, he will solve your present problem as well; even if his current status is “I don’t know.” “I don’t know” is a very good starting point. If this person has solved problems in the past, he will solve your present problem as well; even if his current status is “I don’t know.” Problem-solving is a lot of brain work. Don’t get biased by the lack of visible action. Problem-solving is a lot of brain work. Don’t get biased by the lack of visible action. The success of the solution depends on how well data collection happens. Don’t short-circuit it. The success of the solution depends on how well data collection happens. Don’t short-circuit it. It takes time to provide long-term/permanent solutions for problems. Don’t be like Bart & Lisa with your non-stop “Are we there already?” It takes time to provide long-term/permanent solutions for problems. Don’t be like Bart & Lisa with your non-stop “Are we there already?” It takes time to provide long-term/permanent solutions for problems. Don’t be like Bart & Lisa with your non-stop “Are we there already?” Having identified the problems, the actual process of implementing the solutions has its own set of issues. But that is for some other day to write about. Credit: Photo by Karla Hernandez on Unsplash Credit: Photo by Karla Hernandez on Unsplash Karla Hernandez Unsplash

This Is Why We Suck at Problem-Solving

Deep Lake, a Lakehouse for Deep Learning: Conclusions, Acknowledgement, and References

গভীর লেক, গভীর শিক্ষার জন্য একটি লেকহাউস: উপসংহার, স্বীকৃতি, এবং উল্লেখ

Deep Lake, ein Lakehouse für Deep Learning: Schlussfolgerungen, Danksagungen und Referenzen

Deep Lake, una casa de lago para el aprendizaje profundo: conclusiones, reconocimientos y referencias

Deep Lake, un Lakehouse pour le Deep Learning : conclusions, remerciements et références

डीप लेक, डीप लर्निंग के लिए एक लेकहाउस: निष्कर्ष, स्वीकृति और संदर्भ

ディープラーニングのためのレイクハウス、Deep Lake: 結論、謝辞、参考文献

딥 러닝을 위한 레이크하우스인 Deep Lake: 결론, 감사의 말씀, 참고 자료

Deep Lake, um Lakehouse para Deep Learning: Conclusões, Reconhecimento e Referências

Deep Lake, домик у озера для глубокого обучения: выводы, признательность и ссылки

Deep Lake, Derin Öğrenme için Bir Göl Evi: Sonuçlar, Teşekkür ve Referanslar

Deep Lake, Lakehouse cho Deep Learning: Kết luận, Lời cảm ơn và Tài liệu tham khảo

Deep Lake，深度学习的 Lakehouse：结论、致谢和参考文献

**SHERMAN OAKS, United States, May 14th, 2024/GamingWire/--**Xsolla, a global video game commerce company, published the Spring 2024 edition of "The Xsolla Report: The State of Play” today. Launched on the heels of the Game Developers Conference (GDC) 2024, this extensive report provides invaluable insights into the emerging trends and pivotal shifts impacting the gaming industry in the short and long term.  It sets the stage to significantly shape the future of mobile gaming, deepen academic connections within the gaming ecosystem, and redefine investment patterns. In an era where mobile gaming commanded a 49% share of the global market in 2023, this edition of "The State of Play" sheds light on the evolving landscape of mobile gaming. The report navigates through the advancements in global compliance and regulation, including the Digital Markets Act in Europe's new player engagement strategies, offering a glimpse into the potential future of mobile gaming monetization and distribution. It discusses the impact of cross-platform play and the importance of innovative monetization models, providing actionable insights for developers and industry stakeholders. "The State of Play" emphasizes the importance of academia in the growth and diversification of the gaming industry. It explores how educational programs and initiatives develop talent and promote diversity and inclusivity within the gaming community. This edition underlines the symbiotic relationship between the gaming industry and academic institutions, highlighting programs that significantly impact students and the industry. Berkley Egenes, Chief Marketing and Growth Officer at Xsolla, comments: "As we introduce the latest edition of 'The State of Play,' we're not merely sharing industry insights but advocating for a transformative vision: Equal Access for Everyone. This initiative goes beyond our commitment to innovation and growth within the gaming industry. It's about breaking down barriers to ensure that every developer, regardless of company size, has the opportunity to showcase their creativity and reach a global audience. Our focus is on providing platforms and tools that foster creative opportunities, international exposure, and the development of unique projects, ensuring that the future of gaming is accessible to all. We aim to empower every player and developer worldwide, ensuring the gaming landscape is as diverse and dynamic as its community." The report offers an in-depth analysis of the gaming industry's current investment climate, including funding trends, mergers, and acquisitions. It outlines the shifts in investment patterns, from the heights of the pandemic-induced boom to a more measured approach in 2024. "The State of Play" provides a roadmap for navigating the industry's financial aspects, offering insights into strategic investment opportunities and forecasting future trends. Featuring expert commentary from industry voices like Mukul Aurora, Co-founder of Appsoleut Games; Mariusz Gasiewski, CEO of Mobile Gaming and Apps Lead at Google; Karla Reyes, Founder and Studio Director, Anima Interactive, the Xsolla Report: The State of Play is now available for complimentary download. To secure your copy and gain invaluable insights into the gaming industry, visit our website:  xsolla.pro/txr-spring24 Contact PR Director Derrick Stembridge Xsolla d.stembridge@xsolla.com 919-971-7855 This story was distributed as a release by Gamingwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **SHERMAN OAKS, United States, May 14th, 2024/GamingWire/--**Xsolla, a global video game commerce company, published the Spring 2024 edition of "The Xsolla Report: The State of Play” today. Launched on the heels of the Game Developers Conference (GDC) 2024, this extensive report provides invaluable insights into the emerging trends and pivotal shifts impacting the gaming industry in the short and long term.  It sets the stage to significantly shape the future of mobile gaming, deepen academic connections within the gaming ecosystem, and redefine investment patterns. In an era where mobile gaming commanded a 49% share of the global market in 2023, this edition of "The State of Play" sheds light on the evolving landscape of mobile gaming. The report navigates through the advancements in global compliance and regulation, including the Digital Markets Act in Europe's new player engagement strategies, offering a glimpse into the potential future of mobile gaming monetization and distribution. It discusses the impact of cross-platform play and the importance of innovative monetization models, providing actionable insights for developers and industry stakeholders. "The State of Play" emphasizes the importance of academia in the growth and diversification of the gaming industry. It explores how educational programs and initiatives develop talent and promote diversity and inclusivity within the gaming community. This edition underlines the symbiotic relationship between the gaming industry and academic institutions, highlighting programs that significantly impact students and the industry. Berkley Egenes, Chief Marketing and Growth Officer at Xsolla, comments: "As we introduce the latest edition of 'The State of Play,' we're not merely sharing industry insights but advocating for a transformative vision: Equal Access for Everyone. This initiative goes beyond our commitment to innovation and growth within the gaming industry. It's about breaking down barriers to ensure that every developer, regardless of company size, has the opportunity to showcase their creativity and reach a global audience. Our focus is on providing platforms and tools that foster creative opportunities, international exposure, and the development of unique projects, ensuring that the future of gaming is accessible to all. We aim to empower every player and developer worldwide, ensuring the gaming landscape is as diverse and dynamic as its community." The report offers an in-depth analysis of the gaming industry's current investment climate, including funding trends, mergers, and acquisitions. It outlines the shifts in investment patterns, from the heights of the pandemic-induced boom to a more measured approach in 2024. "The State of Play" provides a roadmap for navigating the industry's financial aspects, offering insights into strategic investment opportunities and forecasting future trends. Featuring expert commentary from industry voices like Mukul Aurora, Co-founder of Appsoleut Games; Mariusz Gasiewski, CEO of Mobile Gaming and Apps Lead at Google; Karla Reyes, Founder and Studio Director, Anima Interactive, the Xsolla Report: The State of Play is now available for complimentary download. To secure your copy and gain invaluable insights into the gaming industry, visit our website: xsolla.pro/txr-spring24 xsolla.pro/txr-spring24 xsolla.pro/txr-spring24 Contact PR Director Derrick Stembridge Xsolla d.stembridge@xsolla.com 919-971-7855 This story was distributed as a release by Gamingwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Gamingwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Xsolla Releases Quarterly Insights Report On The Future Of Gaming And Game Development

A Pivotal Moment in AI : Leaders Rally for a Natural AI Initiative

“What you’re about to see is akin to, I believe, a moment like the launch of the first rocket or the Kitty Hawk moment…So I want you to think about that moment when you first saw something completely new in technology.” — Gabriel Rene, CEO VERSES AI Artificial intelligence is at a critical juncture in its evolution, and today’s LIVE demonstration (November 3, 2023) of VERSES AI’s “Genius™” AI platform showcases a promising new direction for the field. In this presentation, CEO Gabriel Rene and his team provided a first look at how Genius™ is redefining the through its innovative approach rooted in future of AI Active Inference, First Principles AI, and Shared Intelligence. A Departure from Traditional AI Genius™ stands apart from mainstream AI models that rely on static machine learning algorithms trained on massive datasets. Instead, it embraces Active Inference, a technique inspired by biological intelligence. This approach allows Genius™ to adapt and learn in real-time as it interacts with its environment, mirroring the natural processes of the human brain. Demonstrating the Power of Active Inference Genius™ stands apart from mainstream AI models that rely on static machine learning algorithms trained on massive datasets. Instead, it embraces Active Inference, a technique inspired by biological intelligence. This approach allows Genius™ to adapt and learn in real-time as it interacts with its environment, mirroring the natural processes of the human brain. The Role of Hyperspatial Modeling Language (HSML) A key enabler of Genius™’s success is the development of the . This language serves as a bridge between the virtual world and real-world entities, providing a structured format for machines to process multidimensional knowledge. As Gabriel Rene aptly described it, HSML is like “a Google Docs for the real world,” allowing intelligent agents to access and share a coherent representation of reality. Hyperspatial Modeling Language (HSML) The Natural Path to AI The presentation emphasized how Genius™ exemplifies VERSES’ commitment to the “natural path” approach to AI. This approach, inspired by neuroscience, aims to achieve flexible general intelligence that contrasts with the relentless focus on scaling up models seen in the AI industry. By mimicking biological principles, Genius™ strives to create AI that is adaptive, efficient, contextual, and collaborative, bringing AI more in line with human values and goals. The Natural Path to a Smarter World In today’s live demo, VERSES AI’s CEO, Gabriel Rene, unveiled a compelling slide that shed light on the fascinating dynamics shaping the future of artificial intelligence. The slide featured two prominent figures: Dr. Karl Friston on the left and Geoffrey Hinton on the right, both of whom have had a profound impact on the AI landscape. However, what this slide signified was a fundamental distinction that carries immense significance for the future of AI. Dr. Friston, an acclaimed neuroscientist and professor, represents a different path in AI development. His work is not about scaling up machine learning models into behemoth-sized systems but about a more intricate understanding of intelligence based on biological principles. This perspective is exemplified through VERSES AI, the Spatial Web Foundation, and the global core standards being developed through the IEEE. In contrast, the right side of the slide showcases Geoffrey Hinton, a pioneer in machine learning who made significant contributions at DeepMind and Google. His work and the subsequent scaling of neural networks have formed the bedrock of many of today’s and systems. However, as Gabriel Rene pointed out in the presentation, this approach of simply making models larger doesn’t inherently make them more understandable or adaptable. AI generative models While the industry is discussing the idea of scaling models to unimaginable sizes, such as trillions of parameters, the VERSES AI team believes that this path is comparable to casting seeds onto cement — superficially promising but not truly conducive for growth. Larger models tend to become more challenging to interpret, leading to a lack of transparency and explainability. What sets VERSES AI and Dr. Friston’s approach apart is the emphasis on learning in real-time, adaptation, and aligning AI with human goals. This approach mirrors the adaptive nature of living systems and stands in stark contrast to the static, data-centric methods employed by many competitors. In VERSES AI’s view, a single, super-intelligent agent is not the ideal outcome, as it raises questions about control, transparency, and desirability. Instead, VERSES AI envisions a future where AI operates as a distributed ecosystem, distributed across people, systems, and devices. This vision aligns with the concept of “super shared intelligence” rather than a monolithic superintelligence, where collective intelligence enhances human potential. VERSES AI has made significant strides in applying these principles through its Genius™ platform. This platform, which operates as “intelligence as a service,” empowers the creation and orchestration of agents that can learn from experience, understand humans better, and intelligently interact with the real world. In a nutshell, VERSES AI’s approach aims to bring about a smarter world not by scaling up AI but by infusing intelligence into a diverse array of systems, all following the fundamental principles of nature. As the AI landscape continues to evolve, VERSES AI’s commitment to the natural path of AI offers a promising alternative that emphasizes cooperation, adaptability, efficiency, and a holistic understanding of intelligence. This approach could indeed lead to a future where AI is not just smarter but more genuinely aligned with human values and goals, ultimately benefiting society as a whole. The Potential Impact of Genius™ If the live demo lives up to its promises, Genius™ has the potential to revolutionize AI applications across a multitude of industries. VERSES AI’s vision is to make artificial intelligence not only smarter but also safer and more aligned with human objectives. This biomimetic approach, rooted in Active Inference, sets VERSES AI apart as pioneers of a new era in AI. The Path Forward While Genius™ is still in its early stages, VERSES AI has plans to demonstrate its applicability across various domains in the coming months through strategic partnerships. If successful, Genius™ could lead the charge in enabling transformative AI applications, much like the smartphone and the World Wide Web did in their respective eras. VERSES AI’s focus on core innovations in knowledge representation and reasoning sets a new standard for responsible and , offering a promising path towards a future where AI enhances rather than disrupts human society. beneficial AI Check out my blog and tune into my , podcast, Spatial Web AI to learn about Active Inference AI, the Free Energy Principle, and the Spatial Web, where I strive to take these complex topics and make them easy to understand. _to stay up to date with Genius_™ Visit VERSES.AI and Dr. Karl Friston’s revolutionary work with VERSES in the field of Active Inference AI and the Free Energy Principle. Also published . here

VERSES AI Demos ‘Genius™’: Pioneering the Path to Smarter AI

These women have stood out for driving impact solutions in various sectors. Discover how their determination and talent are leaving an indelible mark on the entrepreneurial world and forging a promising future for the new generations. Female participation in business ecosystems worldwide continues to increase, especially when it comes to leadership positions. Historically, this has been a male-dominated industry across this region but it’s clear the tides are starting to turn. A worldwide trend of more and more into the startup and entrepreneurial sectors is being seen across Asia, LatAm, the United States, and Europe, where female innovators are now inspired to seize leadership opportunities, launch their own companies, and support more women to do the same. women moving And this trend is one that’s predicted to have a positive impact on the corporate world in general. A report from highlights that those companies where three or more women fulfill an executive role register higher performance in organizational effectiveness. UN Women Yet being in charge of a team or a company comes with a great deal of responsibility that requires strong, effective leadership. Yet women moving into executive positions also have the added challenge of tackling the historic gender gap and disparities that still exist. For this reason, it’s important to highlight the achievements of who are driving change and creating impact today and in the future. female leaders Here we present 15 female leaders furthering companies that offer everything from financial solutions and educational platforms to workplace tools and healthcare products, all helping to establish women within the fabric of the global economy. , Co-Founder of Nubank Cristina Junqueira Cristina Junqueira is a Brazilian industrial engineer who graduated from the University of São Paulo. After leaving university, she began working as an associate consultant at the Boston Consulting Group while completing a master’s degree in economic and financial modeling. In 2013, Cristina met Colombian David Vélez and, together with Edward Wible, they founded Nubank, one of the largest digital banks in the world valued at $48 billion dollars. , Co-Founder of Gulp Data Lauren Cascio Lauren Cascio is an entrepreneur who stands out as an angel investor and a long-term contributor to the growth of tech ecosystems. Her knowledge and experience make her an influential figure in the industry, motivating and helping new entrepreneurs navigate the complex world of tech startups. Among her latest ventures is Puerto Rico-based startup Gulp Data, a pioneer in data-backed lending and valuations. Gulp Data uses its machine learning technology to quickly assess the value of a company’s data, offering non-dilutive loans using borrower data as collateral to small and medium-sized businesses. , Project Manager at Source Meridian Daniela Gutierrez Tamayo Daniela Gutiérrez Tamayo is a female developer who stands out as a certified Project Manager and Product Owner, specializing in software development and medical data. With 10 years of experience in this field, Daniela played a crucial role in the creation of Source Meridian, a software development company specializing in technology-based life sciences and healthcare technology. Daniela’s dedication in seeking to improve products and processes, guaranteeing punctual deliveries and actively involving employees in decision-making has been essential in fostering solid and successful relationships. , Co-Founder and CEO of StreamWork Meredith Bailey Meredith Bailey has worked in product marketing at major brands including Apple, Google, YouTube and Warner Bros. where she was responsible for developing and launching some of the world’s most beloved technology products. During her career, she has worked on dozens of campaigns and hundreds of creative assets with cross-functional teams. During her time at these large companies, she felt firsthand the pain points when it came to gathering rounds of feedback and approvals from creative stakeholders. This led her to create StreamWork, the first review, approval and project management platform for creative assets. , Founder and CEO of Colorchain Carolina Hernández Carolina Hernández grew up in a family of entrepreneurs in Colombia, with backgrounds in design, textiles, and energy efficiency. She has a unique blend of medical clinical expertise and global business experience. In 2019 she founded Colorchain with the aim of solving the daily apparel challenges that healthcare professionals face using technology, quality materials, and fair labor conditions. The company currently operates in the United States and large parts of Latin America. Recently, Global Health & Pharma recognized Colorchain as the leading provider of medical apparel supplies. , Co-Founder and CEO of Finematter Caroline Chalmer Caroline Chalme launched Finematter in late 2020 with co-founder Mie Ejdrup. Among their investors is Henrik Holmark, former CFO of the Danish jewelry brand Pandora. Finematter is a global platform for fine jewelry, connecting over 60 of the best independent manufacturers with a new, sustainable-minded online audience. The site launched with 20 jewelers and now has over 100 in the US and UK. , Co-Founder at Remoti Daniella Meneses Daniella Meneses is the Director of Growth and Co-Founder of Remoti, with experience building technology teams and products for growing technology companies. From junior software engineers to CTOs, her team improves client satisfaction and retention by ensuring that when clients receive a profile, the candidate has been vetted, qualified, and meets expectations. Remoti is a company that operates in the recruitment and selection segment for global and multinational companies. Remoti allows companies to achieve their expansion goals by carrying out recruitment and selection processes to find the best talent. , Cofounder at Startuptools.ai Sara Ghazi Sara Ghazi is a Co-Founder at Startuptools.ai and is Board Certified Internal Medicine Physician. Founded with the help of Sara and a group of enthusiasts, Startupstools.ai aims to help entrepreneurs simplify and streamline the path from idea to business execution through its AI-based platform. , Co-Founder of TheVentureCity Clara Bullrich Clara Bullrich is a businesswoman who stands out as an influential woman in the world of finance and entrepreneurship. Clara has forged a 17-year career providing investment advisory services, structuring direct investments, contributing to business development and creating new projects in the United States, Latin America and Europe. Clara stands out for her passion for mentoring, helping executive women in both Latin America and the United States chart their path to success. Along with Laura González Estefani, she co-founded the investment fund TheVentureCity to continue supporting new talent. , Co-Founder of Puscar Buritica Family Office Johana Buriticá Johana Buriticá is a woman leader with a faithful conviction for social causes. From her beginnings as founder and editor-in-chief of VamosCowboys through to co-founding of Puscar Buritica Family Office, whose objective is to contribute to the causes that are positively transforming society in Latin America. As an active example of her contribution to change, Johana led the project to donate computers to schools and sectors in need in Colombia, an example of how ideals can be carried out to improve possibilities and open the future to new generations. , Co-Founder and CEO of threshold.world Lina Pérez Lina Pérez is a prominent technology leader and co-founder of the b.world platform, dedicated to improving and promoting those ventures with a social impact approach. Through her experience, Lina has been a pillar in promoting initiatives that deliver positive change for society. As co-founder of b.world, part of threshold.world, Lina has been an inspiring example for the next generation with her commitment to the improvement and support of social enterprises that create pathways towards a more inclusive and sustainable world. , Co-Founder and CEO of Tech Life Saving María Montoya Maria Montoya is an expert in biotechnology and co-founder and CEO of Tech Live Saving (TLS), a company that focuses on the creation of antidotes against snake venom. The company is part of the Tech Innovation Group (TIG) where she also serves as Vice President. María’s work in executing solutions to face the challenges of wildlife and her role in leading investments in emerging sectors make her an outstanding figure in the business and technological sectors. Co-Founder and CCO of Wayru Paula Ceballos, Paula Ceballos is passionate about technology. Together with Charvel Chedraui and Edward Calderón she founded Wayru, an innovative company on a mission to democratize internet access for the urban developing world. Wayru is a decentralized internet network built on the Algorand Blockchain. It’s implemented, operated, and owned by the people. It democratizes Internet access using technologies such as fiber optics, wireless mesh, unlicensed spectrum, and blockchain. , CEMEX Ventures Leaplab Accelerator Program Leader Karla Arrambide Karla Arrambide is a Mexican who currently leads the Leaplab Acceleration Program promoted by CEMEX Ventures, her corporate venture capital and open innovation unit. She has held roles as Corporate Sustainability Manager, Strategic Supply Manager for the Mexico operations, and Global Energy Advisor. Karla has an MBA in Global Business and Strategy from EGADE Business School and the Belk College of Business at the University of North Carolina, as well as a degree in Chemical Engineering from Tecnológico de Monterrey. With her experience in strategy, engineering and global business, Karla helps CEMEX Ventures Leaplab identify startups with innovative value propositions aligned with the investment and sustainability verticals. This article was originally published by on Stiven Cartagena The Sociable.

Female Entrepreneurs Shattering Barriers in 2023

A groundbreaking new artificial intelligence paradigm is gaining momentum thanks to a major discovery proving its underlying scientific theory. What if I told you there is a framework for an entirely new kind of artificial intelligence that is able to overcome the limitations of machine learning AI? I’m talking about an AI that is knowable, explainable, and capable of human governance. One that operates in a naturally efficient way, and does not require big data training. What if this AI was based on the same mechanics as biological intelligence, able to learn in the same way as humans? What if I said that its underlying principles have just been proven to explain the way neurons learn in our brain? This may seem too good to be true, but it’s not. In fact, it’s happening right now. The Future of AI is Shared, Distributed, and Multi-Scale In December 2022, VERSES AI set forth a sweeping vision for artificial intelligence based on a distributed, collective real-time knowledge graph comprised of Intelligent Agents operating on the physics of intelligence itself. In their whitepaper, titled they propose a profound departure from standard notions of as a monolithic system. “Designing Ecosystems of Intelligence from First Principles,” AI Authored by Chief Scientist Dr. Karl Friston and the VERSES AI research team, the paper puts forth the concept of “shared intelligence.” This represents intelligence as emerging from interactions between diverse, distributed nodes as Intelligent Agents, in which each contributes localized knowledge and unique perspectives. Free Energy Principle — A Physics of Intelligence Central to this framework is Friston’s Free Energy Principle (FEP). FEP proposes that neurons are constantly generating predictions to rationalize sensory input. When something doesn’t make sense, these “mismatches” drive learning by updating the brain’s internal model of the world to minimize surprise and uncertainty. This theory neatly explains the remarkable feat of perception and . learning in the brain This provides a unified theory of brain function, proving perception, learning, and inference emerge from internal models that constantly update in this way and that this type of self-organization will follow a pattern that always minimizes the variational free energy in the system. Think of this free energy as the “space of the unknown” between what you think will happen based on what you already know vs. what actually does happen based on things you may not expect. Friston shows how this physics principle can be applied through “Active Inference” to create Intelligent Agents that continually refine their world models by accumulating evidence through experience. In this way, intelligence arises from the process of resolving uncertainty — an intelligence that is self-organizing, self-optimizing, and self-evolving. Biological Mechanisms Validated The trailblazing ideas in the VERSES whitepaper just gained substantial empirical validation. Published in on August 7, 2023, a study from Japan’s Riken Research Institute demonstrated that real neuronal networks do self-organize based on Friston’s Free Energy Principle, proving it correct. Nature Communications By delivering signals to brain cell cultures, researchers showed the emergence of selective responses attuned to specific inputs — confirming predictions of computational models using Active Inference. This concrete in biological neural networks lends tremendous credence to the VERSES AI whitepaper’s proposal of grounding AI in the same neuroscience-based principles. proof Revolutionizing Current AI Methods Mainstream on huge data sets to recognize patterns. However, human cognition operates differently, building an internal intuitive model of how the world works. AI today relies on training neural networks The proposed Active Inference agents similarly maintain generative models rationalizing observations via dynamic beliefs about their causes. This equips AI with common sense and reasoning abilities beyond today’s data-hungry approaches, mitigating machine learning issues like brittleness and opacity. Rather than brute-force machine learning, agents continually update internal models — beliefs of what they know to be true — by interacting with the environment to minimize surprise. Just like humans gather evidence to resolve uncertainty and support our worldview, this allows more efficient and adaptable learning, balancing curiosity and goal achievement. Knowledge Sharing Protocols To enable seamless collaboration, individual agents then connect inside an ecosystem of diverse intelligence within the distributed network of nested collective intelligence, called the Spatial Web, which mimics the distributed functionality of the brain. This allows the frictionless exchange of knowledge and beliefs through a common protocol called Hyperspace Transaction Protocol (HSTP) and a modeling language called Hyperspace Modeling Language (HSML) — a “lingua franca” for AIs to communicate their generative models of the world, linking diverse bits of intelligence. HSML represents all people, places, and things as digital twins in 3D space, informing Intelligent Agents of the ever-changing state of the world. This equips systems with context beyond data, supporting intuitive reasoning. With communication grounded in their internal models, networked AIs develop social abilities like perspective-taking and goal-sharing. This facilitates recurrent self-modeling and value alignment, overseen by human input. The result is a transparent, decentralized intelligence that dynamically self-organizes, bridging individual capabilities in cooperation with each other. The Multi-Scale Aspect is Key The authors of this whitepaper propose that the key to achieving lies not in simply scaling up deep learning neural networks to handle more data and tasks, but rather true intelligence emerges from the interactions of diverse, distributed nodes as Intelligent Agents, and that each contribute localized knowledge and unique perspectives. advanced AI Complex bits of intelligence arise from combinations of simpler intelligence across levels, just as the human mind emerges from interactions among neurons. This allows knowledge to be aggregated while preserving diversity. Each Intelligent Agent in the network contributes its own localized “frame of reference” shaped by its unique experiences and embodiment. Unique localized viewpoints are preserved, as diversity provides selective advantages for the collective system. Intelligence emerges in a distributed way that is transparent, scalable, and collaborative. Energy Efficiency Through Complexity Minimization One of the most fascinating aspects of Dr. Karl Friston’s Active Inference AI, based on the Free Energy Principle, is how it naturally minimizes complexity. Instead of relying on massive data loading, it can take any amount of data and make it smart within the distributed network as individual Intelligent Agents continuously update their internal models. In the same way that the voltages in the brain are quite small, this self-organizing approach works just like natural intelligence, with lower energy requirements. The human adult brain is remarkably energy efficient, operating on In contrast, popular AI systems like ChatGPT have massive energy demands. When first launched, ChatGPT consumed as much electricity as 175,000 brains. With its meteoric rise in use, it now requires the monthly energy of 1 million people. This intense carbon footprint stems from the vast computational resources required to process huge amounts of training data of machine learning. The University of Massachusetts Amherst that “training a single A.I. model can emit as much carbon as five cars in their lifetimes.” referring to a single training instance, yet models are trained repeatedly as they are improved. just 20 watts — less power than a lightbulb. reported The exponential growth of AI is colliding with sustainability. Active Inference AI offers a path to intelligence that minimizes complexity and energy, promising a profoundly scalable and cost-effective path to artificial general intelligence. By mimicking biology, we can nurture AI that thinks and learns while protecting the planet. Roadmap to Artificial General Intelligence The blueprint laid out in the VERSES whitepaper aligns firmly with our understanding of natural cognition. By distributing intelligence while retaining variety and knowledge gained through individual frames of reference, it provides a pathway beyond narrow AI towards adaptable, trustworthy, and beneficial systems exhibiting general intelligence. It’s a system that safeguards and respects individual belief systems, socio-cultural differences, and governing practices. Explainable AI Enables Oversight Crucially, Active Inference AI has also demonstrated the ability for self-introspection and self-reporting as to how it reaches its conclusions. This allows human oversight over otherwise opaque machine learning models. “Explainable AI” Combined with HSML for , the Spatial Web architecture enables human governance to scale alongside AI capabilities. translating human law or norms into code Neuroscience Proof Provides Validation The recent results from Riken substantially boost the credibility of this futuristic framework for AI based on the physics of the brain. The empirical confirmation of the biological mechanisms behind human learning lends increased confidence that systems built on the same principles can achieve human-like robust and generalizable intelligence. By rooting AI firmly in the fundamental laws governing living cognition, this pioneering approach ushers in a new era of explainable, programmable, and collaborative AI, providing a compass for navigating the promise and perils of artificial general intelligence, with unprecedented cooperation between human and machine cognition. Future Implications Spearheaded by VERSES AI, this groundbreaking whitepaper outlines a revolutionary roadmap for artificial intelligence based on collective, distributed intelligence unified through shared protocols within the Spatial Web. This approach fundamentally diverges from current machine learning techniques of standardized neural networks trained on big data. Powered by Karl Friston’s Free Energy Principle, now proven to drive learning in the brain, their vision promises a more human-like AI that is energy efficient, scalable, adaptable, and trustworthy. The Spatial Web architecture provides a framework for frictionless knowledge sharing and oversight through explainable AI models. Combined with the recent neuroscience findings and breakthroughs, this bio-inspired approach could represent the future path to beneficial Artificial General Intelligence, surpassing narrow AI while allowing human values to guide its growth through integrated governance - catalyzing the next evolution of artificial intelligence towards more human-like capabilities. Visit and the to learn more about Dr. Karl Friston’s revolutionary work with them in the field of Active Inference AI and the Free Energy Principle. VERSES AI Spatial Web Foundation Also published . here

New Neuroscience Discovery Validates Groundbreaking AI Whitepaper

Introduction is a newsletter based around clippings from old newspapers where past generations express their concerns about the future and new technologies. Pessimistic Archive In 1859, French poet as*“the refuge of every would-be painter, every painter too ill-endowed or too lazy to complete his studies”* and to embrace it was a sign of and Charles Baudelaire described photography “blindness” “imbecility.” In 1906, the most “ ”, while another writer said that “ ." a writer called love letters written with a typewriter cold-blooded, mechanical, unromantic production imaginable The girl who will put up with a typewritten love letter will put up with anything In the past century, warned against reading in bed, the evils of roller-skating, “bicycle face” which was attributed to “ and the American Society of Composers, Authors and Publishers proved with charts how “ ” had “ ” attention-grabbing newspaper headlines the nervous strain put upon the rider, in keeping his balance”, the talking pictures, radio and the phonograph murdered music. Fast forward to 2023, we have so-called artificial intelligence. It can seamlessly and within seconds generate text, images, videos, and music from text prompts. Many artists are concerned. Three independent visual artists – Sarah Andersen, Kelly Mckernan, and Karla Ortiz - have gone so far as filing with help from lawyer Matthew Butterick and litigators from Joseph Saveri Law Firm. a class-action lawsuit against Stable Diffusion Matthew Butterick is already a known figure in “the legal copyright battle against AI” from , a generative AI tool for code generation. another class-action lawsuit against Github’s CoPilot The Class-Action Lawsuit , I wrote about the open-source AI image generator, Stable Diffusion. The class-action lawsuit is targeted against the owner of Stable Diffusion, Stability AI, another famous AI image company, Midjourney, and the online art community, DevianArt. In my latest post However, the plaintiff’s complaint is formulated in a broad scope and is essentially taking on every generative AI model trained on copyrighted data - which all the big ones are, and in gigantic amounts. In effect, if the San Francisco federal court decides to hear the case on the 19th of July, in spite of , the court’s decision could massively impact a . the defendants’ motions to dismiss multi-trillion-dollar industry Overall, the trio of artists behind the class-action lawsuit is trying to impose a "yes" to two difficult copyright questions generative AI models give rise to - one relating to inputs and one relating to outputs: : Should developers obtain permission and/or pay a license to right holders for using their copyrighted material in the training process of an AI? The input question : If a generative AI product generates output that looks similar to a piece of work created by a human artist, can the right holder make infringement claims against the provider? The output question I am not an expert in US copyright law, just an observer with a neutral stance on the questions. Based on my research, I believe the answer to the first question is "no", while the second question is more problematic to answer, and may depend on a case-by-case assessment. I highly doubt that this class-action lawsuit will provide us with any answers. Another pending copyright case concerning Stable Diffusion’s use and distribution of images in February of this year. was filed by the stock image behemoth Getty Images The lawsuit from Getty Images in my view stands a much better chance of going to court and contributing to the legal understanding of copyrights vs. generative AI. The main difference in one sentence: the Getty Images lawsuit is better documented. Getty Images can prove their rights and point to specific infringements of their rights, whereas the artists behind the class-action lawsuit cannot. The artists' class-action complaint is unfortunately riddled with rudimentary mistakes and wrong assumptions about how Stable Diffusion was trained and how the model generates images. A group of tech enthusiasts has created a website http://www.stablediffusionfrivolous.com/ where they point to some of the technical inaccuracies in the complaint. Here, I will focus on how the artists address, or rather fail to address, the two legal questions as stated above. The Input Question Here is a quote from the complaint (¶57-58), where the artists offer their views on the input question: “Stability scraped, and thereby copied over five billion images from websites as the Training Images used as training data for Stable Diffusion. Stability did not seek consent from either the creators of the Training Images or the websites that hosted them from which they were scraped. Stability did not attempt to negotiate licenses for any of the Training Images. Stability simply took them. Stability has embedded and stored compressed copies of the Training Images within Stable Diffusion.” The first version of Stable Diffusion was trained with “ ” image-text pairs from the public database LAION-5B. CLIP-filtered LAION-5B contains information about 5.85 billion images and is the largest database of its kind. It was developed by the German non-profit organization LAION (an acronym for Large-scale Artificial Intelligence Open Network), and Stability AI helped to fund its development. It’s important to notice that there are not any actual images stored in LAION-5B. Instead, information about each image is stored and consists of: An URL link to the image’s website A short text description of what the image depicts Height and width of the image The perceived similarity to other images a probability score of how likely it is that the image is “unsafe” (pornographic/NSFW) a probability score of how likely it is that the image has a watermark The artists’ claim that Stable Diffusion “stores compressed copies” of their art is therefore a misnomer. In actuality, Stable Diffusion's training dataset consists of metadata about some of the artists’ images, and that metadata is not in itself copyright protected. In the same way a song on Spotify is copyright-protected, but metadata about it such as artist name, song title, producer, release date, genre, and track duration is not. That is because retrieving this data is a purely mechanical process that does not require any creative efforts. As a public dataset, LAION-5B can be examined by anyone interested.  The company has created a search tool where people can search through LAION-5B to see if their images are included in the dataset. Spawning haveibeentrained.com This is what the three artists, Sarah Andersen, Kelly McKernan, and Karla Ortiz did, and they found respectively more than 200, more than 30, and more than 12 representations of their work. Specifically, Stable Diffusion was initially from a subset of LAION-5B called LAION-2B-EN that only contains images with text descriptions in English. trained with 2.3 billion images Considering the size of Stable Diffusions training data, the unwitting contributions made by the three artists are small drops in a vast ocean. In comparison, the Getty Images lawsuit against Stability AI concerned which is still a minuscule part of the entire dataset. more than 12 million photographs from their collection Of all the artists’ works, only 16 images have been registered with the US copyright office by Sarah Andersen. It follows from 17 U.S.C. § 411(a), that “ (..)”. no civil action for infringement of the copyright in any United States work shall be instituted until preregistration or registration of the copyright claim has been made In other words, if a work is not registered with the US copyright office, the right holder can generally not make infringement claims in a civil lawsuit. This means that the artists can only make claims on behalf of the 16 works owned and registered by Sarah Andersen. If only the artists could prove that Stable Diffusion can sometimes generate outputs that resemble any of these 16 images, the artists could perhaps make a case concerning “the output question.” But as we shall see, they are unable to do so. The Output Question In regards to the output question, the artists suggest that every output Stable Diffusion generates is essentially derived from its training data and thereby copyright infringing (see ¶94-95). This legal theory is extremely far-fetched. Below is an illustration from law professor Matthew Sag’s paper “ ” The 15 images to the left are from Stable Diffusions training data with the tags “white”, “coffee” and “cup.” . Copyright Safety for Generative AI The images to the right were generated by Stable Diffusion with the text prompt "coffee cups on white backgrounds.” According to the artists’ logic, all of the images to the right would infringe on the copyright of the images to the left. Although the images do clearly not look substantially similar. Under certain rare conditions, it has been proven that Stable Diffusion in fact can generate output images that look very similar to images from its training dataset. This is especially likely to happen when the input training image is widely distributed on the internet and reoccurs over and over again in Stable Diffusion’s training data. In a recent paper titled Nicholas Carlini and his co-authors identified 350.000 of the most duplicated images in Stable Diffusions training data. Extracting Training Data from Diffusion Models, Hereafter, they generated 500 new images via Stable Diffusion with text prompts identical to the text descriptions associated with each of the training data images. As it turned out, out of the 175 million images (350.000*500), only 109 of the images (0.03%) could reasonably be considered "near-copies.” Thereby, copyright infringements can happen, but the artists do not bring up any examples of how Stable Diffusion has copied their work. On the contrary, they write in the complaint ¶ 93: “ ” In general, none of the Stable Diffusion output images provided in response to a particular Text Prompt is likely to be a close match for any specific image in the training data. The artists do claim that Stable Diffusion is able to mimic their personal artistic styles. Normally, an “artistic style” cannot be subject to copyright protection. Infringement claims always have to be tied to infringements of specific works. However, there is a legitimate issue here that has received Generative AI models can copy the distinctive styles of famous artists in seconds, indefinitely, and with close to zero costs. a fair amount of public attention. To solve this problem, Stability AI removed the names of famous artists from labels in their dataset . This means that Stable Diffusion can no longer mimic people’s artistic styles. as a part of a November upgrade last year If you, for example, ask Stable Diffusion to create an image in the style of Picasso or Rembrandt it is no longer able to do so. The change was initiated two months prior to the class-action complaint. Overall, it is unclear how and why the artists believe Stable Diffusion copies their work. The artists seem more concerned with how Stable Diffusion be able to threaten their jobs in the future, and less concerned with how Stable Diffusion actually works now. might One of the three artists, Sarah Andersen, wrote in from December last year: a NY Times article “I’ve been playing around with several generators, and so far none have mimicked my style in a way that can directly threaten my career, a fact that will almost certainly change as A.I. continues to improve.” Below are two illustrations from the article, one by Sarah Andersen and one by Stable Diffusion.  You can probably guess which one was created by who. Closing Thought In December 2022, that they had partnered up with Spawning, the company behind , and would now provide artists with the option to either opt in or opt out of having their works used as training material for the next version of Stable Diffusion. Stability AI announced haveibeentrained.com Although the initiative , it could be considered a step in the right direction for any artist who is concerned about feeding their work to large foundation models. may not be perfect Prior to the class-action lawsuit, about the new opt-out function, and she did not think Stability AI went far enough: Karla Ortiz talked to MIT Technology Review “The only thing that Stability.AI can do is algorithmic disgorgement where they completely destroy their database and they completely destroy all models that have all of our data in it” This statement is very telling. The three artists behind the class-action law, along with Matthew Butterick and the rest of their legal representation, pretends to stand up for the rights of the artist, but they are in fact modern-day . Luddites

Class-Action Lawsuits Against AI Companies, Modern-Day Luddites, and More

এআই কোম্পানির বিরুদ্ধে ক্লাস-অ্যাকশন মামলা, আধুনিক দিনের লুডিইটস এবং আরও অনেক কিছু

Sammelklagen gegen KI-Unternehmen, moderne Ludditen und mehr

Demandas colectivas contra empresas de inteligencia artificial, luditas modernos y más

Recours collectifs contre les sociétés d'intelligence artificielle, les luddites des temps modernes, etc.

एआई कंपनियों, मॉडर्न-डे लुडाइट्स और अन्य कंपनियों के खिलाफ क्लास-एक्शन मुकदमे

AI企業、現代のラッダイトなどに対する集団訴訟

AI 회사, 현대의 Luddites 등에 대한 집단 소송

Ações judiciais coletivas contra empresas de IA, luditas modernos e muito mais

Yapay Zeka Şirketlerine, Günümüzün Luddite'lerine ve Daha Fazlasına Karşı Toplu Davalar

Các vụ kiện tập thể chống lại các công ty AI, Luddites thời hiện đại, v.v.

针对人工智能公司、现代勒德分子等的集体诉讼

"modesty is the timidity of the body."

This is quite a seminal moment in ’ history. Instead of just another tutorial, I've built an actual tool within the Google Sheets universe. Better Sheets Have you ever thought about taking your Google Sheets experience to the next level by creating your own add-on? In this article, I'll share my story of how I created my first Google Sheets add-on and why you should consider doing it too. Why Create an Add-on? When I first started using Google Sheets, I was intimidated by its capabilities and features. Like very few users press on and see what else it can do. After learning Apps Script, I continued to extend the power of Google Sheets myself. It was empowering. At times it felt like pure raging magic. I've been writing little apps scripts for years. If you know javascript, you know google script. If you're looking to learn how to code in sheets, and you're already an experienced coder, watch this 15 minute video: https://www.youtube.com/watch?v=44B6_svdD9Y?embedable=true Even after coding in sheets for a long time, I was a little intimidated by the prospect of building an add-on from scratch. But with some research, practice, and persistence, I was able to create an add-on that improved my Google Sheets experience and made me more productive. And the best part is, anyone can do it too. I wanted to write an add-on that executed the advice I give many Better Sheets Members. Instead of having to remember my advice, I wished that they could click a button and it happened. The Advice Decrease contrast between your text and background color. Ideally font: #444 and background color #FBFBF8. Doing so makes it almost look like paper. I've done this for years and has helped me deal with eye-strain for long hours. Not My First Try One moment's pause to mention that I did try almost a year ago to make an Add-on and I got stuck in the review process. This time I had a helpful guide. I was helped by Alice Keeler's . great step-by-step article And originally I learned about Apps Script from and . Labnol Digital Inspiration Here's what I made: Sheet Styles It turns your background color, font color, and font family into a pre-created template. I have 4 such styles ready. All of them have less contrast than the black/white Arial combo that is the default Google Sheets style. Less contrast, decreases eye-strain and increase productivity. I wrote a few lines of script that selected the entire active sheet, and changed it to the color I wanted to. I already knew the hex code. The code looked like this var sheet = SpreadsheetApp.getActiveSheet()
    var rowCount = sheet.getMaxRows()
    var colCount = sheet.getMaxColumns()
    sheet.getRange(1,1,rowCount,colCount).setBackground('#fbfbf8')
    sheet.getRange(1,1,rowCount,colCount).setFontFamily('Karla')
    sheet.getRange(1,1,rowCount,colCount).setFontColor('#444')` To make this add-on I created my own HTML sidebar. This was fun for a while until my code just didn't run from the buttons in the sidebar. The key discovery I made was that the side bar does not run google scripts as it says in the documentation, IF the user in sheets is a different user than logged into Chrome. What happens is that there is a deep deep deep error that shows up includes "PERMISSION DENIED". I found a issue tracker for this issue in Google's documentation and found that this issue has not been fixed. The workaround for this was to change the runtime version from "V8" to "DEPRECATED_ES5". Which looks and sounds scary. But it works. Of course maybe in 2017 when this issue first came up there weren't many ways to run multiple google accounts in one chrome, but that is a very common case now. And no longer should be considered an "edge case". I do wish they fix this issue. I tested my code and all works. Why you should make a Google Sheets Add-on: You might want to add integration from your app to sheets. And then also your add-on will be discoverable in the Google Workspace Marketplace. You might want to help yourself. Create an add-on if you have multiple accounts and have some code you want to run in all of them. You can deploy GAS code as a web app, or as a library too. But as an Add-on you can just go and install it easily in any sheet, in anyone's account. It's Your Style You can make an add-on in the flavor of you app. I used custom CSS in my HTML sidebar. Also, you can make a sidebar with the google CSS so it looks and feels more connected to Sheets. This might be useful if you want to put functionality first, and leave your brand behind. In Conclusion Creating a Google Sheets add-on is like going on a wild adventure. Sure, it might be a little scary at first, but once you start exploring and experimenting, you'll discover a whole new world of possibilities. And just like a hero on a quest, you'll overcome obstacles and challenges, and ultimately emerge victorious with a powerful tool that improves your Google Sheets experience and makes you more productive. So why not take the plunge and try your hand at creating a Google Sheets add-on? You never know what amazing things you might discover along the way. There’s even a Dark Mode for you hacker dark mode freaks! Resources so you can build Sheet Add-ons as well Watch this 15 minute . video Alice Keeler's step-by-step article I also first learnt the art of Apps Scripts from reading . Follow him on . Labnol’s blogs Twitter Also published . here

How I Created My First Google Sheets Add-On and Why You Should Try It Too

Over the past six years, a little-known private equity firm, Vista Equity Partners, has built an educational software empire that wields unseen influence over the educational journeys of tens of millions of children. Along the way, The Markup found, the companies the firm controls have scooped up a massive amount of very personal data on kids, which they use to fuel a suite of predictive analytics products that push the boundaries of technology’s role in education and, in some cases, raise discrimination concerns. One district we examined uses risk-scoring algorithms from a company in the group, PowerSchool, that incorporate indicators of family wealth to predict a student’s future success—a controversial practice that parents don’t know about—raising troubling questions. “I did not even realize there was anybody in this space still doing that [using free and reduced lunch status] in a model being used on real kids,” said Ryan Baker, the director of the University of Pennsylvania’s Center for Learning Analytics. “I am surprised and really appalled.” Vista Equity Partners, which declined to comment for this story, has acquired controlling ownership stakes in some of the leading names in educational technology, including EAB, which sells a suite of college counseling and recruitment products, and PowerSchool, which dominates the market for K-12 data warehousing and analytics. PowerSchool alone on more than 45 million children, including 75 percent of North American K-12 students. Ellucian, a recent Vista acquisition, says it . And EAB’s products are . But parents of those students say they’ve largely been left in the dark about what data the companies collect and how they use it. claims to hold data serves 26 million students used by thousands of colleges and universities “We are paying these vendors and they are making money on our kids’ data,” said Ellen Zavian, whose son was required to use Naviance, college preparation software recently acquired by PowerSchool, at Montgomery Blair High School in Silver Spring, Md. After growing concerned about the questions her son was being asked to answer on Naviance-administered surveys, Zavian and other members of a local student privacy group requested access in 2019 to the data the company holds on their children from the district under the Federal Educational Rights and Privacy Act (FERPA). But to date, she has received back only usernames and passwords. “Parents know very little about this process,” she said. The ed-tech companies in Vista’s portfolio appear to operate largely independently, but they have entered into a number of partnerships that deepen the ties of shared ownership. PowerSchool and EAB, for example, have a aimed at “delivering data movement solutions that drive value and save time for Districts.” data integration partnership The two companies also last year that made EAB the exclusive reseller of some PowerSchool products. signed another deal EAB did not respond to requests for comment. To piece together the extent of the companies’ data collection, The Markup reviewed thousands of pages of obtained through public records requests. contracts, user manuals, data sharing agreements, and survey questions We found that the companies, collectively, gather everything from basic demographic information—entered automatically when a student enrolls in school—to data about students’ citizenship status, religious affiliation, school disciplinary records, medical diagnoses, what speed they read and type at, the full text of answers they give on tests, the pictures they draw for assignments, whether they live in a two-parent household, whether they’ve used drugs, been the victim of a crime, or expressed interest in LGBTQ+ groups, among hundreds of other data points. Each Vista-owned company doesn’t necessarily hold all the data points listed here. Some of those data fields were recorded in the traffic between students’ computers and PowerSchool servers when students used their accounts. The Markup reviewed the accounts with students’ permission. Other data fields were listed in districts’ data privacy agreements with PowerSchool and the data library—a list of all available data fields—for one district’s PowerSchool database. Our review offers a more detailed picture of the company’s data operations than PowerSchool publicly discloses, but it is likely an incomplete portrait. According to with school districts, PowerSchool has the right to de-identify the data it holds on their behalf—by removing fields such as names and social security numbers—and use it in any way it sees fit to improve and build its own products. its contracts In some districts, such as Miami-Dade County Public Schools, recent have exceeded $2.5 million for a single year, according to copies of the deals obtained through public records requests. PowerSchool contracts “You don’t pay the oil company to come pump oil off your land; it’s the other way around.” Alex Bowers, Teachers College, Columbia University “It’s hard for me to understand how PowerSchool would not be paying for the privilege” of extracting so much student data, said Alex Bowers, a professor of educational leadership at Columbia University’s Teachers College. “You don’t pay the oil company to come pump oil off your land; it’s the other way around.” PowerSchool declined to answer specific questions about the data it collects and how it uses that information. “At PowerSchool, ensuring student equity, privacy, and access to good quality education is our top priority and is foundational to everything we do,” Darron Flagg, the company’s chief compliance and privacy officer, wrote in a brief statement to The Markup. “PowerSchool strictly and proactively follows legal, regulatory, and voluntary requirements for protecting student privacy including the Family Educational Rights and Privacy Act (FERPA), state regulations, and the Student Privacy Pledge. PowerSchool customers own their student and school data. We do not sell student or school data; we do not collect, maintain, use, or share student personal information beyond what is authorized by the district, parent, or student.” A Cautionary Tale: Elgin, Illinois Many of PowerSchool’s newer product lines, including its predictive analytics tools and personalized learning platform, require troves of student data to train the underlying algorithms. But experts who reviewed The Markup’s findings said that some of the data being used for those purposes is bound to lead to discriminatory outcomes. Consider School District U-46 in Elgin, Ill., which was the only district—out of 27 we submitted public records requests to—that provided a complete list of the data PowerSchool warehouses on its behalf. The district also provided documents detailing how PowerSchool’s predictive analytics algorithms draw on some of that data to influence students’ educational journeys. U-46’s PowerSchool database contains nearly 7,000 data fields about Elgin students, parents, and staff, according to a The Markup obtained. copy of the data library As early as first grade, algorithms from the company’s Unified Insights product line start generating predictions about whether students are at low, moderate, or high risk of not graduating high school on time, not meeting certain standards on the SATs, or not completing two years of college, among other outcomes. The district’s documents describe available via PowerSchool, although U-46 says it does not use most of them. dozens of different predictive models The district begins displaying student on-time graduation risk scores to teachers and administrators beginning in seventh grade, according to Matt Raimondi, Elgin’s assessment and accountability coordinator. Free and reduced lunch status—a proxy for family wealth—and student gender are among the most important factors in determining that risk score, according . At one point, Elgin’s models—developed by a company called Hoonuit that was acquired by PowerSchool in 2020 and rebranded as Unified Insights—also variable. to the documents incorporated student race as a heavily weighted Flagg, from PowerSchool, said race was removed from the models in 2017 before the company acquired Hoonuit. The predictive models also draw on data points like attendance, disciplinary history, and test scores. Learning analytics experts told The Markup that the use of demographic data like gender and free and reduced lunch status—attributes that students and school officials can’t change—to predict student outcomes is bound to encode discrimination into the predictive models. “I think that having [free and reduced lunch status] as a predictor in the model is indefensible in 2021,” said Baker of the University of Pennsylvania’s Center for Learning Analytics. Baker has consulted with BrightBytes, a competitor of PowerSchool in the K-12 predictive analytics space. “Unified Insights does provide the option for school districts to include free and reduced lunch status to enable districts to reduce dropout risk associated with economic hardship and identify additional social service supports that may be available to impacted students,” Flagg, from PowerSchool, wrote in an email. “Including these things that are not within the control of the family or the school is highly problematic,” said Bowers, from Columbia University Teachers College, because even the best-intentioned school cannot change all the systemic gender and wealth disparities that affect a particular student. Basing the risk scores so heavily on those factors therefore obscures the impact of other factors a school may be able to influence, he said. Raimondi said U-46 has chosen not to use many of the predictive models PowerSchool makes available because of their reliance on immutable student characteristics “Especially down at the early grades, we don’t even make it visible to any users besides myself and a programmer,” he said. “The models at the lower grades, they’re not that accurate and they rely a lot more heavily on demographic-type data.” Each year, Elgin’s dropout risk model misses about 90 students in each grade level, out of 3,000 students per grade, who do not go on to graduate on time, according to a by a PowerSchool data scientist and obtained by The Markup. presentation prepared “We have no comment on the sensitivity/specificity of the models,” U-46 spokesperson Karla Jiménez wrote in an email. The Markup on a similar dropout prediction tool EAB sells to colleges and universities. Some of those schools incorporated race as a “high impact predictor” of success, and their algorithms labeled Black students “high risk” at as much as four times the rate of their White peers, effectively steering students of color away from certain majors. has previously reported After our reporting, Texas A&M University as a predictive variable. dropped the use of race The Data Empire Is Growing Vista Equity Partners has been expanding its reach in the educational software industry for years. Along with that expansion, it’s put together a portfolio of companies that amass data and effectively track kids throughout their educational journeys. Since 2015, when Vista first purchased PowerSchool from Pearson for $350 million, Vista has been on a spending spree, acquiring other ed tech companies that collect different kinds of student data. In 2017, PowerSchool bought SunGard K-12, which provided human resources and payroll software for schools. In 2019, it purchased Schoology, a widely used learning management system that served as the digital backbone for many schools’ curricula and lesson plans. It acquired Hoonuit, which provides the predictive risk scoring used by districts like Elgin, in 2020. Last March, it completed the purchase of the college preparatory software Naviance, and in November, it purchased Kickboard, a company that collects data about students’ behavior and social-emotional skills. In , PowerSchool officials have said more acquisitions are a key part of the company’s growth plan. presentations to investors EAB has been on a similar purchasing spree, acquiring companies like Wisr, YouVisit, Cappex, and Starfish that are used for college recruitment, advertising, and tracking students on campus. It also announced the , a “next-generation data warehouse and analytics hub” designed to “break down data silos.” creation of Edify Last June, Vista , which sells a variety of educational technology products. The company claims to serve more than 26 million students across 2,700 institutions. also acquired a co-ownership stake in Ellucian That consolidation of data and power has triggered a backlash from privacy-minded parents, some of whom have been trying, unsuccessfully, to find out what the deals mean for their children’s sensitive data. Piercing the veil of secrecy can be difficult, even when parents turn to privacy laws designed to increase transparency. Illinois, for example, has a state law that requires school districts to post specific information about the ed-tech vendors they use, including all written agreements with vendors and lists of the data elements shared with those vendors. Despite that, districts like Chicago Public Schools have pertaining to PowerSchool and Naviance. CPS has, however, posted data use disclosures for other vendors. Across Illinois, 5,800 schools use PowerSchool software, . yet to post any of the required material according to the company FERPA has also proven of little use for some parents. Cheri Kiesecker, a Colorado parent of two, said that she requested her children’s records under the law from PowerSchool earlier this year after it completed the Naviance deal. “Each school district owns and controls access to its students’ data,” Flagg, from PowerSchool, wrote in an email to The Markup. “Any requests from parents for access to their children’s data must be managed through their respective school districts. '“Our children aren’t products.” Deborah Simmons, parent PowerSchool instructed Kiesecker to request the records through the school, which she did. When PowerSchool did not comply with the school’s subsequent request by the statutory 45-day deadline, her school’s attorneys sent a legal demand to the company, which The Markup reviewed. To date, Kiesecker said, she has still not received her children’s complete records, although PowerSchool has provided partial documentation. Deborah Simmons, a Texas parent, said she began looking into the Vista-owned companies after discovering that her school had automatically uploaded her child’s data into Naviance. She filed public records requests and grievances with her school but still doesn’t know the full extent of the data the companies hold or who else it’s been shared with. “These tech companies want to eliminate the data silos and merge and streamline all of this stuff, but no, our children aren’t products,” Simmons said. That’s what they do, they treat our children like products. They’re human beings and they deserve privacy and freedom.” Written by: Todd Feathers Photo by on Jonas Jacobsson Unsplash Also published here

Your Children's Data Is Being Collected by Educational Technology Companies  

Note: Shyft participated in this event in a judging/mentoring capacity and has also supported other blockchain hackathons. We’re not organizers of ETHDenver. Community Gathering Buildathon The blockchain ecosystem is at a point where collaboration and education are essential in order to accelerate the learning curve and encourage wider adoption. did a great job at positioning the event based on what the audience needed the most: a community gathering fully focused on building new Ethereum solutions and products to further push that tech envelope, and to learn from each other. ETHDenver So what can other hackathons learn from ETHDenver? Here are 7 tips to consider when organizing your next event: 1. Accommodations at the venue Participants in the hackathon, stewards, and mentors spend a huge amount of hours or even full days at the venue. Their minds are constantly stimulated, be it for coming up with innovative ideas for your project or for learning new concepts from workshops. To make sure they keep their energy levels just as high, there need to be proper accommodations for them at the venue. ETH Denver made sure participants never lacked fuel to keep going. The venue was essentially turned into a food show, where Colorado producers could show off their new local products. Additionally, food trucks were serving international meals in exchange for DaI tokens that were airdropped to each attendee. Turning the venue into a big open playground definitely helped the community feels going. There were hidden rooms to discover (like the Garden of Ether and the yoga room); a scavenger hunt for stickers that made participants interact with the exhibiting companies; art galleries; kombucha and food stations to socialize around; even a chill room with 24/7 live music. Each hack break could turn into a new encounter, a new discovery, and lots of new spontaneous connections. There was also plenty of space to sit down and relax while enjoying some music and art. 2. Daycare for the win! We really need to highlight this beautiful and thoughtful initiative. This is the first time ever that we’ve seen a daycare service in a crypto event…and we’ve been to a lot of them! Crypto events, conferences, and hackathons generally go for 2–3 days, usually over the weekend. This means that if you have a family, has to stay with the kids at home during one of these days, and often, it’s women who end up staying at home and opting out of participating. This year, ETHDenver introduced a new standard that we’d love to see many other events in this space emulate. It was a success, and we did see many happy moms leaving their children at play while participating in the event. What a fantastic idea. someone 3. Central Location The venue was located at the heart of Denver, right on the main drag, perfect for attendees who stay in downtown locations nearby. There were plenty of restaurants, museums, galleries and parks, just a short walk away so you could easily do sightseeing and exercising during breaks and after hours. 4. Keep it fun On-site activities kept participants entertained during the weekend. The buffircon stickers collection helped to gamify the hackers’ interactions with presenting sponsors. For each table visited, they collected a special sticker to be added to the event water bottle. Once all stickers were collected, participants could claim a hard wallet. The two art galleries were also a great way to interact with cryptocurrency while supporting artists. There was an option to pay in crypto or bid on the blockchain for your favorite art, with half the funds going to non-profits like Aprrent.io, who provide workshops and educational programs for kids. 5. Have lots of support on site Large hackathons often attract many young developers and beginners who have never taken on such a challenge before. To make it fun and enjoyable for them, it’s essential to have lots of mentors and educators. On the #BUIDL floor, ETH Denver had a mentor table, where an experienced professional was available to answer general questions. There were also mentors assigned to different tracks. Many stewards volunteered their time and were present during the entire run of the hackathon to ensure everyone had a great experience. Weekend-long hackathons can be exhausting for participants, as it’s a huge challenge to come up with original ideas and build prototypes from scratch in this massively constrained time frame. When event organizers recognize this and make an effort to keep everyone hydrated, give them food and make sure they have a good time in between, everybody wins — and builds. 6. Keep it educational Having mentors on-site + 80 hours of workshops and keynotes scheduled on the agenda enabled builders to gain new skills and learn new things. The talks covered an array of topics, from technical to design and marketing, and there was something for everyone, for beginners and more advanced builders alike. 7. Make a positive impact From providing a special educational track for kids to supporting local artists and developing a special social impact track with support from UNICEF, ETHDenver ensured that communities around the world could benefit from the collective talent pool. The Shyft team was on the ground to mentor and judge the that promoted projects built for social good, structured around the UN’s Global Sustainable Development Goals. Impact Track Overall, based on our previous experience with similar events, ETHDenver brought a lot of innovative and creative options to the table to engage the community. It was a great experience, and we look forward to seeing what the hackathons of the future have in store. _View Karla Vilhelem's profile on LinkedIn, the world's largest professional community. Karla has 11 jobs listed on…_www.linkedin.com Karla Vilhelem - PR and Events at Shyft Network | LinkedIn *** Shyft is building a general purpose proof of sender protocol for instant trust generation and portability, for any definition of sender, designed to integrate across organizations and governments with expertise in identity verification. Shyft is a credentials verification platform. Join our Telegram ( https://t.me/shyftnetwork ), follow us on Twitter ( https://twitter.com/shyftnetwork ), GitHub ( https://github.com/ShyftNetwork ) and other channels found on https://www.shyft.network

7 tips hackathons can pick up from ETHDenver

Each week, we share five simple actions to create a more inclusive workplace and be a better ally. 1. Buck unconscious demotions This week, we saw another glaring example of an unconscious demotion. It’s what happens when, upon meeting someone new, one might assume they’re in a lower role or position because of their gender. Or skin color. Or other visible indication that they’re a member of a marginalized group. Massachusetts State Representative Tram Nguyen was on the receiving end of one of these demotions, : which she shared on Twitter body[data-twttr-rendered="true"] {background-color: transparent;}.twitter-tweet {margin: auto !important;} Lobbyist: Are you Rep X's aide? Me (in full suit): No. Lobbyist: Are you Rep Y's aide? Me: No. I'm Rep Nguyen. Lobbyist: Oh, you're Rep Nguyen's aide. Me: No! I'm the representative. This is why we need more women, and #WOC in leadership positions. #RepresentationMatters — @TeamTram function notifyResize(height) {height = height ? height : document.documentElement.offsetHeight; var resized = false; if (window.donkey && donkey.resize) {donkey.resize(height); resized = true;}if (parent && parent._resizeIframe) {var obj = {iframe: window.frameElement, height: height}; parent._resizeIframe(obj); resized = true;}if (window.location && window.location.hash === "#amp=1" && window.parent && window.parent.postMessage) {window.parent.postMessage({sentinel: "amp", type: "embed-size", height: height}, "*");}if (window.webkit && window.webkit.messageHandlers && window.webkit.messageHandlers.resize) {window.webkit.messageHandlers.resize.postMessage(height); resized = true;}return resized;}twttr.events.bind('rendered', function (event) {notifyResize();}); twttr.events.bind('resize', function (event) {notifyResize();});if (parent && parent._resizeIframe) {var maxWidth = parseInt(window.frameElement.getAttribute("width")); if ( 500 < maxWidth) {window.frameElement.setAttribute("width", "500");}} The next time you meet someone for the first time, ask an open-ended question about their work. Use this technique to combat bias that might otherwise have you demoting them unconsciously. 2. Don’t hold existing hiring processes as sacrosanct Karla Monterroso, CEO of Code2040, about how they’re shifting their strategy based on learnings over 6 years of creating a pipeline to improve racial equity in tech. As Karla shared: wrote a Twitter thread body[data-twttr-rendered="true"] {background-color: transparent;}.twitter-tweet {margin: auto !important;} What we found is that the structural barriers to entry for Black and Latinx people meant that though we had a thriving population of talent we had supported in gaining access to the industry, the industry itself was not ready to change and allow the talent in it's doors. — @Code2040 function notifyResize(height) {height = height ? height : document.documentElement.offsetHeight; var resized = false; if (window.donkey && donkey.resize) {donkey.resize(height); resized = true;}if (parent && parent._resizeIframe) {var obj = {iframe: window.frameElement, height: height}; parent._resizeIframe(obj); resized = true;}if (window.location && window.location.hash === "#amp=1" && window.parent && window.parent.postMessage) {window.parent.postMessage({sentinel: "amp", type: "embed-size", height: height}, "*");}if (window.webkit && window.webkit.messageHandlers && window.webkit.messageHandlers.resize) {window.webkit.messageHandlers.resize.postMessage(height); resized = true;}return resized;}twttr.events.bind('rendered', function (event) {notifyResize();}); twttr.events.bind('resize', function (event) {notifyResize();});if (parent && parent._resizeIframe) {var maxWidth = parseInt(window.frameElement.getAttribute("width")); if ( 500 < maxWidth) {window.frameElement.setAttribute("width", "500");}} One of their learnings: Some tech companies weren’t willing to change their hiring process to be less biased. They saw their process as sacrosanct. As allies, let’s all be open to feedback. Let’s strive to understand where people from underrepresented groups drop out of our hiring pipeline, and take action to change those steps to be more inclusive and less biased. 3. Realize it’s not on THEM to find YOU, but on YOU to find THEM If you’re a hiring manager or in a senior leadership role at your company, reflect on what you personally are doing to attract candidates from underrepresented groups. How are you expanding your network to be more diverse? Are you stepping outside of your comfort zone to meet people from other races, genders, socio-economic situations, sexual orientations, and more? As we learned in by Treehouse CEO Ryan Carson, it’s not on them to find us. By contrast, it’s on us to find them. this article in Fast Company 4. Identify year-round actions to support black colleagues February is Black History Month in the US and Canada. While it’s a helpful reminder , why not identify systemic, year-round actions to take that will last well beyond February? to celebrate the people and important events in the history of the African diaspora For example, if you’re a white person, Select books by black authors to read throughout during 2019 Subscribe to a podcast by a black host or one that features black guests Reach out to your black employee group and offer to be a mentor Identify professional events for black people that you will attend this year (checking first with the event’s web site or organizers to make sure you’d be welcome). 5. If you make a mistake, apologize, learn, and take action Being an ally is a journey, and one where you’re bound to make mistakes (because you’re human). When you make a mistake, don’t double down on your stance. Instead, share a heartfelt apology and discuss how you can do better. In fact, we made a mistake this week that we want to share with you. Here’s what happened: If you follow @betterallies on Twitter, you know that we tweet the actions for our weekly newsletter, often in advance of the publication date. A few days ago, we tweeted action #4 from this newsletter (above). However, , we used “POC” instead of “black.” E.g., “Select books by POC authors to read during 2019.” in our tweet Katrina Jones, Head of D&I at Twitch, immediately : replied body[data-twttr-rendered="true"] {background-color: transparent;}.twitter-tweet {margin: auto !important;} Suggestion here - since these actions are in recognition of Black History Month, and meant to extend action beyond this honorary month, replace "POC" with "black". Broadening to "POC" might diminish the desired impact @betterallies — @Katrina_HRM function notifyResize(height) {height = height ? height : document.documentElement.offsetHeight; var resized = false; if (window.donkey && donkey.resize) {donkey.resize(height); resized = true;}if (parent && parent._resizeIframe) {var obj = {iframe: window.frameElement, height: height}; parent._resizeIframe(obj); resized = true;}if (window.location && window.location.hash === "#amp=1" && window.parent && window.parent.postMessage) {window.parent.postMessage({sentinel: "amp", type: "embed-size", height: height}, "*");}if (window.webkit && window.webkit.messageHandlers && window.webkit.messageHandlers.resize) {window.webkit.messageHandlers.resize.postMessage(height); resized = true;}return resized;}twttr.events.bind('rendered', function (event) {notifyResize();}); twttr.events.bind('resize', function (event) {notifyResize();});if (parent && parent._resizeIframe) {var maxWidth = parseInt(window.frameElement.getAttribute("width")); if ( 500 < maxWidth) {window.frameElement.setAttribute("width", "500");}} We’re so grateful to Katrina for pointing this out. We learned from her, and we took action by . tweeting an improved version Being an ally is a journey. Want to join us? 😍 Follow @betterallies on , , , or . Twitter Medium Instagram Pinterest ✉️ This content originally appeared in our newsletter, . to get it delivered to your inbox every Friday. 5 Ally Actions Subscribe 📖 Read the book. Better Allies 👕 Get your Better Allies gear Together, we can — and will — make a difference.

Bucking Unconscious Demotions and Sacrosanct Hiring Processes, plus Other Actions for Allies

from broad strokes to the lore to the stories to the tangents to the UNIX, these are must reads for every hacker. The tech industry has a bad case of memory loss these days. Luckily, previous generations of the industry (along with journalists and academics) have done a pretty good job of cataloguing and contextualizing our history for us. If you have any interest in engaging in or interacting with the tech industry, knowing the history gives you the upper hand. With that in mind, here are my picks for the minimum set of volumes you should read, in order to get a general idea of the important bits of computer history. The broad strokes , by Thomas Rid Rise of the Machines , by James Gleick The Information The lore , by Karla Jennings The Devouring Fungus , by Eric S. Raymond The New Hacker’s Dictionary , by Kevin Kelly Out of Control , by Douglas Rushkoff Microserfs , by Neal Stephenson In the Beginning… Was the Command Line , by M. Mitchell Waldrop Man-Made Minds Stories , by George Dyson Turing’s Cathedral , by Steven Levy Hackers: Heroes of the Computer Revolution , by John Markoff What the Dormouse Said , by Michael Swaine and Paul Freiberger Fire in the Valley , by Theodor Holm Nelson Possiplex , by Tim Berners-Lee Weaving the Web Tangents , by Jon Gertner The Idea Factory , by Stephen Johnson Interface Culture UNIX , by Eric S. Raymond The Art of Unix Programming , by Simson Garfinkel, Daniel Weise, and Steven Strassman The Unix Haters Handbook is how hackers start their afternoons. We’re a part of the family. We are now and happy to opportunities. Hacker Noon @AMI accepting submissions discuss advertising &sponsorship To learn more, , , or simply, read our about page like/message us on Facebook tweet/DM @HackerNoon. If you enjoyed this story, we recommend reading our and . Until next time, don’t take the realities of the world for granted! latest tech stories trending tech stories

18 book reading list for computer history

"Deep Learning is Rubbish"
 Karl Friston & Yann LeCun's Panel at the Davos 2024
World Economic Forum

“The collective progress in this field showcases Active Inference’s potential as a systematic blueprint for Artificial General Intelligence (AGI).” As Chief Scientist at and pioneer of the Free Energy Principle that underlies Active Inference, Friston and his VERSES team have developed an entirely new kind of that mimics biological intelligence, able to take any amount of data and make it ‘smart.’ VERSES AI AI In an exclusive presentation at the recent held in Ghent, Belgium, this past September 13–15, 2023, world-renowned neuroscientist Dr. Karl Friston gave fewer than 100 global Active Inference experts and researchers a glimpse into the future of next-generation artificial intelligence. His talk provided perspective into some of the latest research related to state spaces, universal generative models, belief sharing between agents, active learning, and structured learning. 4th International Workshop on Active Inference (IWAI) Dr. Friston is at the forefront of developing ‘Active Inference’ models, revolutionizing how intelligent systems learn and adapt. The information shared at IWAI is built on more than a decade of groundbreaking work and collaboration with fellow researchers in the at University College London. Nested Minds Network Watch the full episode NOW on or . YouTube Spotify The Fabric of Intelligence: State Spaces and Factor Graphs At the heart of understanding intelligence lies the idea of ‘generative world models’ — these are probabilistic frameworks that encapsulate the underlying structure and dynamics involved in the creation of sensory data. As Friston explained, developing a that can be widely applied has been a core pursuit. universal generative world model The challenge lies in modeling the intricacies of ‘state spaces’ — capturing not just sensory data itself but the hidden variables and control factors that determine how stimuli unfold over time. By incorporating hierarchical and factorial structure, increased temporal depth, and an emphasis on Agent dynamics and control paths, Friston has worked to construct expressive yet interpretable models of complex environments. As he suggested, the resulting grammar of cognitive machinery — factor graphs equipped with message passing — may provide a foundation for advancing distributed and embedded intelligence systems alike. Exploring the Nature of State Spaces A significant portion of the talk focused on state spaces within these generative models. Friston highlighted how understanding these spaces is vital for grasping the dynamics of how our brain predicts and reacts to stimuli. Friston has focused heavily on developing more complete generative models of disputed state spaces, generalizing and expanding on partially observed Markov decision processes. His models place special emphasis on representing paths and control variables over time, while accounting for a variety of factors that can operate independently or in conjunction with each other, across different layers or levels of the model. The direct modeling of dynamics and control in his work sheds new light on understanding concepts like intentional planning as opposed to behaviors influenced by prior preferences. hierarchical framework through various time scales, Emergent Communication Systems Among Multiple Agents . Friston showed that when Intelligent Agents pursue ‘active learning’ with a focus on gaining information, this approach inherently leads to the development of common communication methods and linguistic structures. Essentially, as Agents strive to enhance their model’s accuracy and effectiveness by exchanging beliefs, self-organized patterns evolve, spontaneously establishing a basis for mutual understanding and predictability. Intelligence also relies on interacting with other Agents Developing methods for seamlessly pooling knowledge and achieving consensus while retaining specialization is an active research direction. The integrated components must balance stability with flexibility, adapting core beliefs slowly while remaining receptive to external influences. As Friston noted, much like human maturational trajectories, childlike malleability fades, yet the integration of new ideas remains possible through niche environments. Assembling a Universal Generative World Model A universal ‘world model’ that can be widely applied remains an ambitious goal. Friston discussed two potential approaches — an initially simple model that grows structurally to capture more complexity versus a massively interconnected model that relies more on attentional spotlights. He also noted the potential for composing such models from subgraphs of specialized Intelligent Agents, allowing for parallel development of appropriately-scoped pieces. Belief sharing through communication protocols, such as the developed by VERSES AI, enables the learning Agents to converge on a mutually predictable, and thereby more efficient, joint world model. Spatial Web Protocol Belief Sharing Through Active Learning Belief sharing and its impact on active learning formed another cornerstone of Dr. Friston’s presentation. He revealed how our brains share and update beliefs, a process central to learning and adapting to new environments. In his talk, Friston demonstrated belief sharing in an example with multiple Intelligent Agents playing a hiding game. This emergent communication system arises naturally from the drive to maximize the information and efficiency of the shared world model. By actively learning the mapping between beliefs and communicative utterances, the Agents can resolve uncertainty and synchronize their internal models via the utterances that propagate beliefs. Information-Theoretic Insights into Active Learning In a more technical sense, Friston views active learning as a process where updates to the model are seen as actions aimed at reducing expected free energy. This perspective is rooted in information theory, with free energy representing the gain in information, bounded by certain preferences that arise from updating specific parameters. As a result, the model learns mappings that are both sparse and rich in mutual information, effectively representing structured relationships. Friston illustrated this through a simulation of Intelligent Agents jointly self-organizing around a shared language model. Structured Learning: A New Perspective Finally, structured learning was discussed as a novel approach within the realm of . Dr. Friston provided insights into how structured learning frameworks could offer more efficient ways of understanding and interacting with the world. active inference Structured Learning through Guided Model Expansion Friston explored active model selection, framing the expansion of a model’s structure as similar to goal-directed optimization through expected free energy. Gradually introducing new elements, such as states or factors, following simple heuristic principles, allows for the automatic expansion of the model’s complexity, to better reflect and improve its alignment with the learning environment. Friston demonstrated applications ranging from unsupervised clustering to the development of distinct, non-overlapping representations in an Agent simulation. Structured Deep Learning Intelligence requires not just statistical modeling, like what we see in current AI machine learning/deep learning systems, but recognizing structural composition — the patterns of parts to wholes and dependencies that characterize natural systems that occur in the real world. Friston outlined strategies for progressively evolving the architecture of real-world models and making improvements to modular elements in response to fresh data, all centered around clear goals. The guided increase in complexity astonishingly leads to the natural development of organized and distinct feature areas, classifies them into clear categories, and controls their behavior patterns, all from raw multimedia data streams. Such capabilities get closer to flexible human-like learning that moves far beyond the current passive pattern recognition systems of today, into Autonomous Intelligent Systems interacting with and reshaping their environments. The Future of Active Inference AI Overall, Dr. Karl Friston’s presentation at IWAI 2023 demonstrates that his work continues to push Active Inference AI into new territory through innovations like inductive planning, information-theoretic formalisms, emergent communication systems, and structured learning. As the models, methods, and insights mature, the prospects grow ever stronger for realizing artificial intelligence as multitudes of Intelligent Agents that can learn, act, and cooperate at the level of human intelligence. The collective progress in this field showcases Active Inference’s potential as a systematic blueprint for Artificial General Intelligence (AGI). While Friston’s presentation was meant only as a glimpse, The foundation of Dr. Karl Friston’s impact in the realm of AI is driven by his clarity of vision and deep intellectual insight that are actively shaping the evolution of this next era of these technologies. these insights keep VERSES AI at the leading edge of creating Autonomous Intelligent Systems (AIS) that can understand, communicate, and adapt as humans do. Watch NOW on : YouTube Episode Chapters: 00:00 — Introduction by Tim and Karl Friston’s Opening Remarks 06:09 — The Significance of Free Energy in Understanding Life 07:10 — Exploring Markov Blankets and Factor Graphs 09:56 — Hierarchical Generative Models and Time Perception 13:36 — Active Inference and Planning with Expected Free Energy 15:40 — Joint Free Energy and Generalized Synchrony in Physics 16:40 — The Role of Paths and Intentions in Physics and Active Inference 17:35 — Specifying Endpoints of Paths as Goals 30:26 — Communication and Belief Sharing in Federated Systems 31:35 — Generative Models and Perception in Agents 40:19 — Model Comparison and Latent State Discovery 41:25 — Active Model Selection and Handwritten Digit Styles 45:30 — Structured Learning and Object Localization 49:10 — Epistemic Foraging and Confidence in Learning 50:21 — The Dynamics of Information Gain and Learning 51:29 — Conclusion and Q&A Begins 01:19:33 — Emphasis on Constraints in the Free Energy Principle 01:23:40 — Closing Remarks 01:24:55 — Karl Friston’s Reflections on the Field’s Evolution and the Next Generation , and Explore the future of AI with Active Inference and gain insights into this revolutionary approach! 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