The document discusses how thinking small and open innovation through platforms like Arduino have enabled new models of innovation. It notes how Arduino started as a cheap, open-source electronics platform and has now sold over 60,000 units worldwide. However, it also discusses challenges with scaling from prototypes to production and new manufacturing, financial, and market models needed to support small-scale innovation.
At any given time, with all the knowledge we have, new knowledge can emerge. We call this the adjacent possible. It explains why new inventions are invented when they are, and why they are not possible before. Adjacent possible is a very useful term to understand the progress of technology. Technology evolves by using prevailing technologies to improve upon. Thus technology is combinatorial and built in layers. With each layer new ideas can be built upon the previous layers. Thus Gall´s Law says that any complex system that works is built of simpler systems that work.
We will look at the adjacent possible and some ideas that came when all the enabling technologies are available. We also look at an idea that was not possible to build at the time, Charles Babbage engines.
At any given moment it is easy to look back to see how technology has changed over time. At the same time it is difficult to see what transformations are taking place in current moment, and even more difficult to see where things are going.
We will explore what technology is. For us it may be the latest tech stuff we see, something new. But what about everyday objects that we take for granted. Are those not technologies also?
How does technology evolve and where did it come from? We look at some ideas on evolution of technology and how it is similar to biology in some ways. We will also look at the origin of the word technology. Finally we will define the term we will use in the course. Terms defined are technology, product performance, and innovation to name few.
At any given time, with all the knowledge we have, new knowledge can emerge. We call this the adjacent possible. It explains why new inventions are invented when they are, and why they are not possible before. Adjacent possible is a very useful term to understand the progress of technology. Technology evolves by using prevailing technologies to improve upon. Thus technology is combinatorial and built in layers. With each layer new ideas can be built upon the previous layers. Thus Gall´s Law says that any complex system that works is built of simpler systems that work.
We will look at the adjacent possible and some ideas that came when all the enabling technologies are available. We also look at an idea that was not possible to build at the time, Charles Babbage engines.
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
Skype talk given at the first Internet of Things meetup in Wellington on November 4th 2014.
http://www.meetup.com/Wellington-Internet-of-Things-IoT-Meetup/events/208303962/
When innovators try to envision how people will use their product they often have different ideas on what people want. Products that are of superior technology may fail and inferior succeed, only because the inferior product has some features that people are looking for.
In this lecture we look at how new products or technologies get adopted my markets. We look at the Law of Diffusion of Innovation, which explains how this adoption happens. We also look at what it takes for a new innovation to move from being a visionary idea to a practical product, or crossing the chasm. Finally we explore the hype cycle.
In this lecture we look at how innovation happens. We look at the slow hunch, the liquid network, the hummingbird effect, and serendipity.
At any given moment it is easy to look back to see how technology has changed over time. At the same time it is difficult to see what transformations are taking place in current moment, and even more difficult to see where things are going.
We will explore what technology is. For us it may be the latest tech stuff we see, something new. But what about everyday objects that we take for granted. Are those not technologies also?
How does technology evolve and where did it come from? We look at some ideas on evolution of technology and how it is similar to biology in some ways. We will also look at the origin of the word technology. Finally we will define the term we will use in the course. Terms defined are technology, product performance, and innovation to name few.
Slides for September 26th Internet of Things Webinar I ran for RS to kick off their new Internet of Things Design Centre we contributed content to. bit.ly/IOT-Webinar
At any given time, with all the knowledge we have, new knowledge can emerge. We call this the adjacent possible. It explains why new inventions are invented when they are, and why they are not possible before. Adjacent possible is a very useful term to understand the progress of technology. Technology evolves by using prevailing technologies to improve upon. Thus technology is combinatorial and built in layers. With each layer new ideas can be built upon the previous layers. Thus Gall´s Law says that any complex system that works is built of simpler systems that work.
We will look at the adjacent possible and some ideas that came when all the enabling technologies are available. We also look at an idea that was not possible to build at the time, Charles Babbage engines.
At any given moment it is easy to look back to see how technology has changed over time. At the same time it is difficult to see what transformations are taking place in current moment, and even more difficult to see where things are going.
We will explore what technology is. For us it may be the latest tech stuff we see, something new. But what about everyday objects that we take for granted. Are those not technologies also?
How does technology evolve and where did it come from? We look at some ideas on evolution of technology and how it is similar to biology in some ways. We will also look at the origin of the word technology. Finally we will define the term we will use in the course. Terms defined are technology, product performance, and innovation to name few.
At any given time, with all the knowledge we have, new knowledge can emerge. We call this the adjacent possible. It explains why new inventions are invented when they are, and why they are not possible before. Adjacent possible is a very useful term to understand the progress of technology. Technology evolves by using prevailing technologies to improve upon. Thus technology is combinatorial and built in layers. With each layer new ideas can be built upon the previous layers. Thus Gall´s Law says that any complex system that works is built of simpler systems that work.
We will look at the adjacent possible and some ideas that came when all the enabling technologies are available. We also look at an idea that was not possible to build at the time, Charles Babbage engines.
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
Skype talk given at the first Internet of Things meetup in Wellington on November 4th 2014.
http://www.meetup.com/Wellington-Internet-of-Things-IoT-Meetup/events/208303962/
When innovators try to envision how people will use their product they often have different ideas on what people want. Products that are of superior technology may fail and inferior succeed, only because the inferior product has some features that people are looking for.
In this lecture we look at how new products or technologies get adopted my markets. We look at the Law of Diffusion of Innovation, which explains how this adoption happens. We also look at what it takes for a new innovation to move from being a visionary idea to a practical product, or crossing the chasm. Finally we explore the hype cycle.
In this lecture we look at how innovation happens. We look at the slow hunch, the liquid network, the hummingbird effect, and serendipity.
At any given moment it is easy to look back to see how technology has changed over time. At the same time it is difficult to see what transformations are taking place in current moment, and even more difficult to see where things are going.
We will explore what technology is. For us it may be the latest tech stuff we see, something new. But what about everyday objects that we take for granted. Are those not technologies also?
How does technology evolve and where did it come from? We look at some ideas on evolution of technology and how it is similar to biology in some ways. We will also look at the origin of the word technology. Finally we will define the term we will use in the course. Terms defined are technology, product performance, and innovation to name few.
Slides for September 26th Internet of Things Webinar I ran for RS to kick off their new Internet of Things Design Centre we contributed content to. bit.ly/IOT-Webinar
Flupa UX Days 2017 : "What's diffrent about UX for IOT" par Claire RowlandFlupa
Helping users form an effective mental model of the system: what different devices do, and how they are interconnected. When is it appropriate to explain the system model – how things actually work – and when to simplify so they don’t need to concern themselves with technical details?
Effective composition: distributing functionality between devices, to suit the capabilities of the devices and context of use.
Appropriate consistency: how to determine which elements of the design should (and should not) be consistent across different interfaces, considering e.g. terminology, platform conventions, aesthetic styling and interaction architecture.
Continuity: how patterns of connectivity unique to IoT can cause discontinuities in the UX between devices, and how to handle these in the design.
Das «Internet of Things» ist definitiv ein Hype-Thema - immer wieder hört man von innovativen Anwendungen. Erfunden werden diese oft von Bastlern. So entstehen aus Do-it-Yourself-Projekten Open Source Hardware Startups. Die Anwendungen werden mit Raspberry Pi oder Arduino gebaut und mittels Crowdfunding finanziert.
Referent Thomas Amberg zeigte in seinem Referat spannende Produkte, die aus der Open Source Bewegung entstanden sind.
How Web Design will reinvent manufacturingMike Kuniavsky
Picture a world where Amazon.com is a factory. Products are made as needed, based on direct input from users to designers and developers. Consumption directly drives production, and data informs design. If we weren't talking about physical products, this would sound a lot like Web/app interaction design, but the worlds of making atoms and bits are quickly colliding, and the implications are profound. By mapping what we have learned creating analytics-driven digital design to the physical world, we can change how everything is made, for the better.
Flupa UX Days 2017 : "What's diffrent about UX for IOT" par Claire RowlandFlupa
Helping users form an effective mental model of the system: what different devices do, and how they are interconnected. When is it appropriate to explain the system model – how things actually work – and when to simplify so they don’t need to concern themselves with technical details?
Effective composition: distributing functionality between devices, to suit the capabilities of the devices and context of use.
Appropriate consistency: how to determine which elements of the design should (and should not) be consistent across different interfaces, considering e.g. terminology, platform conventions, aesthetic styling and interaction architecture.
Continuity: how patterns of connectivity unique to IoT can cause discontinuities in the UX between devices, and how to handle these in the design.
Das «Internet of Things» ist definitiv ein Hype-Thema - immer wieder hört man von innovativen Anwendungen. Erfunden werden diese oft von Bastlern. So entstehen aus Do-it-Yourself-Projekten Open Source Hardware Startups. Die Anwendungen werden mit Raspberry Pi oder Arduino gebaut und mittels Crowdfunding finanziert.
Referent Thomas Amberg zeigte in seinem Referat spannende Produkte, die aus der Open Source Bewegung entstanden sind.
How Web Design will reinvent manufacturingMike Kuniavsky
Picture a world where Amazon.com is a factory. Products are made as needed, based on direct input from users to designers and developers. Consumption directly drives production, and data informs design. If we weren't talking about physical products, this would sound a lot like Web/app interaction design, but the worlds of making atoms and bits are quickly colliding, and the implications are profound. By mapping what we have learned creating analytics-driven digital design to the physical world, we can change how everything is made, for the better.
Talk given at the London Design Festival's Global Design Forum on September 20th 2022.
https://londondesignfestival.com/activities/keynote-regenerative-bursts
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
New economies of innovation
1. The new economy of innovation
How thinking small got big
Alexandra Deschamps-Sonsino
CEO & Co-Founder of Tinker.it!
LIFT Marseille Vendredi 19 Juillet 2009
2. Tinker.it!
Design studio in London & Milan
Physical computing
Interactive products & installations
www.tinker.it
3. Massimo Banzi
CTO of Tinker.it!
Co-Founder of
the Arduino platform
www.arduino.cc
15. We should Let me ask Let’s have
make the design a meeting
Ax1
>> department
>>
Ok send the Hmm, that’s Let’s have
specs to the not really what a meeting
engineering
>> we asked for
>> & establish
department. requirements
Let’s email Let’s get this That just cost
them a >> prototyped with >> €10K
document the CNC machine
17. I want I spend
Let me Google
to make >> that for you >> some €
Ax1
I make a I post it on I link to
prototype >> my blog >> it on Twitter
Make blog 10 people
links to it >> want to buy it >> Now what?
http://makezine.com/
25. The point
Rethinking how innovation happens
Supporting small businesses
Shared innovation models
Funding for small projects
Reboot local production
26. Merci à LIFT!
Alexandra Deschamps-Sonsino
alex@tinker.it
twitter.com/tinker_it
www.tinker.it
www.tinker.it/now
LIFT Marseille 2009