BBC SemWeb panel: Where does OpenID fit in?Dan Brickley
This document summarizes a panel discussion on the Semantic Web and BBC that included the following:
1) A 5 minute introduction on the Semantic Web project which aims to add semantics and meaning to documents on the web to make their contents more machine-readable.
2) A 5 minute discussion on how OpenID fits into the Semantic Web and allows for identity and authentication on the web.
3) A 5 minute scenario section discussing potential applications of linking data with relationships and meanings on the Semantic Web.
4) A 5 minute discussion on the challenges of timing for new technologies like the Semantic Web.
Открытая лекция в Санкт-Петербурге про городскую картографию, 14 апреля 2016
Интеллектуальный кластер «Игры разума»
Ссылки на проекты, из презентации:
https://github.com/minikarma/geotalk/blob/master/links.md
Urbica is a design firm based in Moscow that focuses on human experience design in cities. They conduct user experience research, information design, spatial data analysis, and urban planning. Their approach involves prototyping and getting user feedback. Some of their projects include designing maps for MAPS.ME, analyzing bike rental data for the Moscow Department of Transport, studying New York City's bike share rebalancing system, and researching pedestrian conditions in Moscow.
BBC SemWeb panel: Where does OpenID fit in?Dan Brickley
This document summarizes a panel discussion on the Semantic Web and BBC that included the following:
1) A 5 minute introduction on the Semantic Web project which aims to add semantics and meaning to documents on the web to make their contents more machine-readable.
2) A 5 minute discussion on how OpenID fits into the Semantic Web and allows for identity and authentication on the web.
3) A 5 minute scenario section discussing potential applications of linking data with relationships and meanings on the Semantic Web.
4) A 5 minute discussion on the challenges of timing for new technologies like the Semantic Web.
Открытая лекция в Санкт-Петербурге про городскую картографию, 14 апреля 2016
Интеллектуальный кластер «Игры разума»
Ссылки на проекты, из презентации:
https://github.com/minikarma/geotalk/blob/master/links.md
Urbica is a design firm based in Moscow that focuses on human experience design in cities. They conduct user experience research, information design, spatial data analysis, and urban planning. Their approach involves prototyping and getting user feedback. Some of their projects include designing maps for MAPS.ME, analyzing bike rental data for the Moscow Department of Transport, studying New York City's bike share rebalancing system, and researching pedestrian conditions in Moscow.
2 часть презентации «Визуальные коммуникации» агентства SHISHKI.
Презентиация о грамотной визуализации идей и структурировании визуальной информации, выбор оптимального соотношения текстовой и изобразительной информации. Определение наиболее эффективных средств коммуникации в зависимости от аудитории и медийного канала.
Работа с фоном, цветом и формой графического контента, инфографика в презентациях.
Выступление в рамках блока «Визуальные коммуникации» Всероссийской школы презентаций и коммуникаций.
Презентиация о грамотной визуализации идей и структурировании визуальной информации, выбор оптимального соотношения текстовой и изобразительной информации. Определение наиболее эффективных средств коммуникации в зависимости от аудитории и медийного канала.
Работа с фоном, цветом и формой графического контента, инфографика в презентациях.
Карты и визуализация данных (Dribbble Meetup 2015 @ Mail.ru HQ)Andrey Karmatsky
Презентация выступления на Dribbble Meetup 2015 (23 мая, в офисе Mail.ru)
Видеозапись выступления: https://youtu.be/NwadfbF2Nlw?list=PLcJ8pdaABCSnp_U-jan68olnacuLmVHRs
Подборка ссылок на проекты, которые показывались в презентации: https://github.com/minikarma/geotalk/blob/master/links.md
Мы сделали новую версию интерфейса Яндекс.Карт, и пытались выстроить процесс работы в условиях когда хотелок очень много, а мир бежит быстрее нас.
Презентация с выступления на WhaleRider-2013 (1 окт.) с комментариями для листания.
Есть идея проецировать указатели в сложных переходах на пол или на стены. Кажется, этот проект способен малыми усилиями сделать подземные переходы в городе удобнее и понятнее для ориентирования.
Андрей Кармацкий: «Картографический дизайн Яндекса»Andrey Karmatsky
Коротенький рассказ о том, как мы разрабатываем дизайн Яндекс.Карт. Какие из особенностей требуется учитывать, какие есть при этом проблемы.
На примере проекта по редизайну карты Москвы расскажу основные принципы информационного дизайна.
2 часть презентации «Визуальные коммуникации» агентства SHISHKI.
Презентиация о грамотной визуализации идей и структурировании визуальной информации, выбор оптимального соотношения текстовой и изобразительной информации. Определение наиболее эффективных средств коммуникации в зависимости от аудитории и медийного канала.
Работа с фоном, цветом и формой графического контента, инфографика в презентациях.
Выступление в рамках блока «Визуальные коммуникации» Всероссийской школы презентаций и коммуникаций.
Презентиация о грамотной визуализации идей и структурировании визуальной информации, выбор оптимального соотношения текстовой и изобразительной информации. Определение наиболее эффективных средств коммуникации в зависимости от аудитории и медийного канала.
Работа с фоном, цветом и формой графического контента, инфографика в презентациях.
Карты и визуализация данных (Dribbble Meetup 2015 @ Mail.ru HQ)Andrey Karmatsky
Презентация выступления на Dribbble Meetup 2015 (23 мая, в офисе Mail.ru)
Видеозапись выступления: https://youtu.be/NwadfbF2Nlw?list=PLcJ8pdaABCSnp_U-jan68olnacuLmVHRs
Подборка ссылок на проекты, которые показывались в презентации: https://github.com/minikarma/geotalk/blob/master/links.md
Мы сделали новую версию интерфейса Яндекс.Карт, и пытались выстроить процесс работы в условиях когда хотелок очень много, а мир бежит быстрее нас.
Презентация с выступления на WhaleRider-2013 (1 окт.) с комментариями для листания.
Есть идея проецировать указатели в сложных переходах на пол или на стены. Кажется, этот проект способен малыми усилиями сделать подземные переходы в городе удобнее и понятнее для ориентирования.
Андрей Кармацкий: «Картографический дизайн Яндекса»Andrey Karmatsky
Коротенький рассказ о том, как мы разрабатываем дизайн Яндекс.Карт. Какие из особенностей требуется учитывать, какие есть при этом проблемы.
На примере проекта по редизайну карты Москвы расскажу основные принципы информационного дизайна.
Информационные бюллетени Яндекса и другие исследования
Выбрать исследования по теме:
Россия на электронной карте
(информационный бюллетень по данным службы Яндекс.Карты и поиска Яндекса на осень 2009)
Основные факты:
* В России более 170 тысяч населённых пунктов.
* Самое распространённое название — Александровка. По данным Яндекс.Карт, так называются 166 российских населённых пунктов. «Новых», «Верхних» и «Больших» населённых пунктов в России больше, чем «Старых», «Нижних» и «Малых».
* Самые популярные названия улиц — Лесная, Центральная и Садовая. Улица Ленина занимает только 23 строку рейтинга.
* Среди всех объектов городской инфраструктуры пользователей поиска Яндекса больше всего интересуют магазины.
* И в городах-миллионниках, и в городах с меньшей численностью населения средняя длина улицы одна и та же — 900 метров.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
3. «We have these things called computers, and
we’re basically just using them as really fast paper
emulators.»
«The important thing isn’t thinking about
computers or programming as they are today, but
thinking about moving from a static medium like
marks on paper to a dynamic medium with
computational responsiveness infused into it, that
can actually participate in the thinking process.»
Bret Victor