Vazamentos massivos nas redes sociais: quais medidas os usuários devem tomar?ESET Brasil
Realizamos uma pesquisa com os nossos usuários para obter informações sobre os vazamentos massivos nas redes sociais e as principais medidas tomadas ao se deparar com incidentes desse tipo. Confira um infográfico com os principais dados deixados pela pesquisa.
Vazamentos massivos nas redes sociais: quais medidas os usuários devem tomar?ESET Brasil
Realizamos uma pesquisa com os nossos usuários para obter informações sobre os vazamentos massivos nas redes sociais e as principais medidas tomadas ao se deparar com incidentes desse tipo. Confira um infográfico com os principais dados deixados pela pesquisa.
Slides for the SF Python meetup tutorial Introduction to Deep Learning. The tutorial goes over a simple code that trains a fully connected neural network to classify handwritten digits from the MNIST dataset.
Associated Github repo:
https://github.com/Dataweekends/intro_deep_learning_sf_python_meetup
Truth table, Karnaugh map & logic circuit with 5 outputs and 8 inputsAbir Chowdhury
This is the Logic circuit which enables taking the MW data from the consumers to the substation, separating them into two major categories: a fixed cost for any 4 loads, and cost will increment from 5th load onwards.
Design is as good (or flawed) as the people who make itKayla J Heffernan
Talk given at UX Australia 2016 held in Melbourne.
ABOUT THE TALK:
No one sets out to intentionally design a system that is hard to use for - or worse, excludes or discriminates against - some users. Designers are trying their best. You're probably a good person, but a human nonetheless, therefore not perfect. Design can only be as good as the people who make it. Conversely, design is as flawed as the people who make it.
ABOUT THE SPEAKER:
Kayla Heffernan is a user and experiencer of products, frustrated with mediocrity and a passionate advocate for the voice of all users. Kayla is a UX designer at SEEK and also undertaking a PhD in Interaction Design looking at digital insertables. In her spare time… she doesn’t have any.
This ppt describes one of the interesting algorithms to count the number of bits set in an unsigned integer.
x = (x & 0x55555555) + ((x>>1)&0x55555555));
x = (x&0x33333333) + ((x>>2)&0x33333333);
...
....
In-silico study of ToxCast GPCR assays by quantitative structure-activity rel...Kamel Mansouri
The EPA tested several thousand chemicals in 700 toxicity-related in-vitro HTS bioassays through the ToxCast and Tox21 projects. However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in-silico methods, and quantitative structure-activity relationships (QSARs) are a cost effective approach to predict biological activity. The overall goal of this project was to use QSAR predictions to fill the data gaps in a larger environmental database of ~30K structures. The specific aim of the current work was to build QSAR models for multiple ToxCast assays using a subset of 1800 chemicals tested in 18 G-Protein Coupled Receptor (GPCR) assays. These assays are part of the aminergic category which was among the most active within the biochemical assays. Using PLSDA for the human histamine H1 GPCR assay, the classification accuracy reached 94% with a non-error rate of 89% in fitting and 80% in 5-fold CV, with only 2 latent variables. These results demonstrate the ability of QSAR models to predict bioactivity.
Artificial Intelligence is on the rise. Most of us do not understand the fundamental effects of AI, let alone the brain behind it. Let us build a grassroots movement and fight for transparent AI tech.
Artificial Intelligence is the hot tech paradigm of the moment. It is the subject of a great deal of media hype, woes and mythologising. It seems worthwhile, therefore, to try to set the scene, look at some definitions, and see where it is currently being applied.
Not Dead Yet: Designing Great Experiences with Bad DataSonia Koesterer
By Sonia Koesterer
The world is imperfect. Every “happy path” intersects with dozens of crappy paths caused by typos, technical errors, and data that goes missing, is mis-assigned, adulterated, or is otherwise compromised/ stolen by evil data pirates. While you can’t prevent all data fails, you can avoid catastrophic failures, design graceful recoveries, and even turn the weakest points of your service into a strategic advantage. In short, you can create great services despite bad data.
The impact of data failure can be a humorous accident, minor inconvenience, or completely detrimental. For example, each year, the U.S. government falsely declares over 12,000 people dead due mostly to typos. In sheer percentage this is a rarity of a corner case of an edge case… but for those 12,000 individuals who suddenly lose their social security benefits, health insurance, bank accounts, and can’t easily prove they are alive, it’s catastrophic.
So design for the the edge-case! Understand the weakest points of your service, learn from them, and turn your failures into great experiences.
Slides for the SF Python meetup tutorial Introduction to Deep Learning. The tutorial goes over a simple code that trains a fully connected neural network to classify handwritten digits from the MNIST dataset.
Associated Github repo:
https://github.com/Dataweekends/intro_deep_learning_sf_python_meetup
Truth table, Karnaugh map & logic circuit with 5 outputs and 8 inputsAbir Chowdhury
This is the Logic circuit which enables taking the MW data from the consumers to the substation, separating them into two major categories: a fixed cost for any 4 loads, and cost will increment from 5th load onwards.
Design is as good (or flawed) as the people who make itKayla J Heffernan
Talk given at UX Australia 2016 held in Melbourne.
ABOUT THE TALK:
No one sets out to intentionally design a system that is hard to use for - or worse, excludes or discriminates against - some users. Designers are trying their best. You're probably a good person, but a human nonetheless, therefore not perfect. Design can only be as good as the people who make it. Conversely, design is as flawed as the people who make it.
ABOUT THE SPEAKER:
Kayla Heffernan is a user and experiencer of products, frustrated with mediocrity and a passionate advocate for the voice of all users. Kayla is a UX designer at SEEK and also undertaking a PhD in Interaction Design looking at digital insertables. In her spare time… she doesn’t have any.
This ppt describes one of the interesting algorithms to count the number of bits set in an unsigned integer.
x = (x & 0x55555555) + ((x>>1)&0x55555555));
x = (x&0x33333333) + ((x>>2)&0x33333333);
...
....
In-silico study of ToxCast GPCR assays by quantitative structure-activity rel...Kamel Mansouri
The EPA tested several thousand chemicals in 700 toxicity-related in-vitro HTS bioassays through the ToxCast and Tox21 projects. However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in-silico methods, and quantitative structure-activity relationships (QSARs) are a cost effective approach to predict biological activity. The overall goal of this project was to use QSAR predictions to fill the data gaps in a larger environmental database of ~30K structures. The specific aim of the current work was to build QSAR models for multiple ToxCast assays using a subset of 1800 chemicals tested in 18 G-Protein Coupled Receptor (GPCR) assays. These assays are part of the aminergic category which was among the most active within the biochemical assays. Using PLSDA for the human histamine H1 GPCR assay, the classification accuracy reached 94% with a non-error rate of 89% in fitting and 80% in 5-fold CV, with only 2 latent variables. These results demonstrate the ability of QSAR models to predict bioactivity.
Artificial Intelligence is on the rise. Most of us do not understand the fundamental effects of AI, let alone the brain behind it. Let us build a grassroots movement and fight for transparent AI tech.
Artificial Intelligence is the hot tech paradigm of the moment. It is the subject of a great deal of media hype, woes and mythologising. It seems worthwhile, therefore, to try to set the scene, look at some definitions, and see where it is currently being applied.
Not Dead Yet: Designing Great Experiences with Bad DataSonia Koesterer
By Sonia Koesterer
The world is imperfect. Every “happy path” intersects with dozens of crappy paths caused by typos, technical errors, and data that goes missing, is mis-assigned, adulterated, or is otherwise compromised/ stolen by evil data pirates. While you can’t prevent all data fails, you can avoid catastrophic failures, design graceful recoveries, and even turn the weakest points of your service into a strategic advantage. In short, you can create great services despite bad data.
The impact of data failure can be a humorous accident, minor inconvenience, or completely detrimental. For example, each year, the U.S. government falsely declares over 12,000 people dead due mostly to typos. In sheer percentage this is a rarity of a corner case of an edge case… but for those 12,000 individuals who suddenly lose their social security benefits, health insurance, bank accounts, and can’t easily prove they are alive, it’s catastrophic.
So design for the the edge-case! Understand the weakest points of your service, learn from them, and turn your failures into great experiences.
Imagine a culture where the input of the whole organization turns an individual idea into a user story in just a couple of hours, where everybody's goal is to make the customer’s job easier and more effective, and where you work on projects you love instead of projects you loathe. A great coding culture concentrates on making developers productive and happy by removing unnecessary overhead, bringing autonomous teams together, helping the individual programmer to innovate, and raising awareness among developers about how to create better code.
I will talk about how to establish and foster a strong engineering-focused culture that scales from a small team to a huge organization with hundreds of developers. I'll give lots of examples from our experience at Atlassian to show that once you're working in a great coding culture, you won't want to work anywhere else.
https://www.youtube.com/watch?v=TAk04-_M-JM&feature=youtu.be
Lecture 4: How it Works: Convolutional Neural NetworksMohamed Loey
We will discuss the following: Filtering, Convolution, Convolution layer, Normalization, Rectified Linear Units, Pooling, Pooling layer, ReLU layer, Deep stacking, Fully connected layer.
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
Do you have a lot of complex jobs that you need to run as part of your application? Do they consist of multiple tasks and you wonder how to orchestrate them properly? Do you want to be able to easily scale their execution? Is availability of your workers important to you? If you answer “Yes” to these questions then AWS Simple Workflow is the right tool for you.
In this talk we will go through Amazon SWF and Java Flow Framework and you will see how to get a distributed job execution engine right out of the box. We will also compare SWF to alternative solutions, discuss real life experience, and of course enjoy a live demo.
The talk will be most useful to everyone who is interested in the design of distributed systems and is new to AWS SWF.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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/
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.