"In Vain have you acquired knowledge if you have not imparted it to others." Deuteronomy Rabbah
As information exchange is increasingly happening online and optimized through interconnected technologies that business prosper, the trade-offs between the central principles and values were discussed: focused on how Tech resources could be used for the benefit of society to improve collective sustainable ecosystems
- able to create systems that enforce and guarantee the rights that are necessary to maintain a free and open society .
Ecosystems can be symbiotic or parasitic : ecological relationship cocreate value, capable of shaping the market ; wherever economics serve the people and not otherwise -bridging the 'discursive gap' between policy text and practice ( unleashing social innovation for societal benefit ) .
On the one hand, there is a wide gap between the pace of law and technology - on the other, there are also different types of Democracy and interpretation views.
When the physicist Stephen Hawking told an audience in Portugal during a talk at the Web Summit technology conference in Lisbon, Portugal, in which he said,
“computers can, in theory, emulate human intelligence, and exceed it.”
he was alerting that AI’s impact could be cataclysmic unless its rapid development is strictly and ethically controlled:
“Unless we learn how to prepare for, and avoid, the potential risks,” he
explained,
“AI could be the worst event in the history of our civilization.” Hawking explained that to avoid this potential reality, creators of AI need to “employ best practice and effective management.”
- "Is Your AI Ethical? " - Responsible A.I. Has a Bias Problem, and Only Humans Can Make It a Thing of the Past: As more company’s adopt A.I., more issues will surely come to the forefront.
Many business are already working toward making changes that will stop A.I. problems before they go any further. It relies on several key technologies, such as machine learning, natural language processing,
rule-based expert systems, neural networks, deep learning, physical robots, and robotic process automation. Some AI applications have moved beyond task automation but still fall well short of context awareness.
Responsible AI is defined as the integration of ethical and responsible use of AI into the strategic implementation and business planning process:
transparent and accountable AI solutions that create better service provision. Such solutions harness, deploy, evaluate and monitor AI machines, thus helping to maintain individual trust and minimize privacy invasion.
“As A.I. systems get more sophisticated and start to play a larger role in people’s lives, it’s imperative for business to develop and adopt clear principles that guide the people building, using and applying A.I.” ;
“We need to ensure systems working in high-stakes areas such as autonomous driving and health care will behave safely and in a way that reflects human values.”
The event held the debate on major technological forces , currently driving to digital disruption on the medium Cloud, Social Movements (power of transmission and repetition of the message) on mobile, Big Data and IoT,
are Transforming Physical Security in the Digital Age - In a world where Citizens are not products, clients or customers - rather reshape public human rights , and the Economy represents a tool we humans invented
- like democracy and politics - to help govern our relationships between each other - ourselves with nature and the world we live in.
If these tools aren't getting the outcomes that make us happy, safe, healthy, better educated and protecting / preparing our country for an increasingly uncertain future , as quality of life is stagnating; unfair , jobs and health education Systems, regardless of how much money you have or where you live; while our environment is suffering, then it's time our economic tools change to embrace transformative policies that reprioritise our investments.
However, the use of AI within many industries, from banking to finance, manufacturing to operations, retail to supply chain - changed the way industries operate.
In social media environments - digital marketers, created a new way to connect and engage with the target audience or media marketing performance. In oposition, it raised ethical concerns and eventually carries the risk of attracting consumers’ distrust - extracting harmful marketing appeals, lack of transparency, information leakage and identity thef.
Developing AI solutions should consider human rights, fairness, inclusion, employment and equality can lead to potential gains in credibility for products and brands - ensure brand safety and protect consumers from fraud and the
dissemination of fake information, thus increasing customer trust towards brands. Recognizing the value of sensitive data and the harm that could be caused if certain data were to fall into the hands of the wrong parties, many governments and industries have established laws and compliance standards by which sensitive data must be Pseudonymized or Anonymized.
Europe is putting pressure on internet companies like Facebook and Google to safeguard against hate speech, trolling, cyber-bullying, fake news, sex traffickers online and terrorist activities online.
The GDPR (general data protection regulations act - OM MAY 4 2020) passed by the parliament of the EU aims to safeguard the data privacy rights of its citizens.
While the act combined with the EU court’s “Right to be forgotten” judgment has set precedence in the way companies handle the data of their consumers.
Individuals now have the "right of data portability", the "right of data access" along with the "right to be forgotten" and can withdraw their consent whenever they want , as well as intrusive online brand presence.
" Social media marketing is in transition as AI and analytics have the potential to liberate the power of social media data and optimize the customer experience and journey. Widespread access to consumer-
generated information on social media, along with appropriate use of AI, have brought positive impacts to individuals, organisations, industries and society " (Cohen, 2018).
-- Considering the conscious principles of compromise, chain potentially relevant questions about General Data Protection Regulations ::
" How are organisations ensuring that the content posted by staff and consumers does not compromise the ethical principles of the brand - managing their social media presence in line with data protection and privacy regulations ?
What do you need to protect : on whatever occasion the adversary gains access to information that is sensitive to you? What are the risks of compromise and how to mitigate them ? What practices and mechanisms can enable firms to cultivate an ethical culture of AI use
/ How can digital marketing professionals ensure that they utilize AI to
deliver value to the target customers with an ethical mindset? "
Examples of Seeking capital - information, social, and cultural Individuals - are applied whenever companies join uses of artificial intelligence for recruitment or machine-learning systems like In the process of
seeking various types of capital through digital marketing platforms, consumers experience both positive (benefits) and negative (costs ) effects.
The velocity of information flow, volume of information shared, network clusters and cross-posts on different social media may be analyzed and compared for negative and positive electronic word-of-mouth.
These intra-interaction consequences such as consumers’ cognitive, emotional, and behavioral engagement with the brand thus trigger extra-interaction consequences of brand trust and attitude thus developing brand equity through the DCM strategy.
This often leads to confusion ( 'discursive gap' ) about when and how to deploy what information technology, to maximize value creation opportunities during stages of
the customer journey - as it usually questions:
" What is the interplay between customer traits (e.g. innovativeness, brand involvement, technology readiness) and attributes of technological platforms in this process? What firm capabilities are required to capture, manage and exploit these innovation opportunities from customers to gain a deeper
understanding of them?"
---- Since There are different Types of Data: Nominal, Ordinal, Discrete, Continuous, Interval and Ratio scale -- The Netflix’s dynamic optimizer example, attempts to improve the quality
of compressed video, but gathers data - initially from human viewers
- and uses it to train an algorithm to make future choices about video transmission, with the aim to deliver personalized and
targeted experiences to multiscreen audiences to keep them coming back -
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AI is progressing in Broadcast & Media, through some mainstream applications , to uncover patterns that aren’t always intuitive to human perception and able to change consumer behaviours - the two most viewer-centric applications would be on content discovery and content personalization :
Netflix’s new AI tweaks each scene individually to
make video look good even on slow internet - It also tracks the movies we watch, our searches, ratings, when we watch, where we watch, what devices we use, and more. In addition to machine data,
Netflix algorithms churn through massive amounts of movie data that is derived from large groups of trained movie taggers ; Google Is Using Artificial Intelligence to Make Sure YouTube Content Safer for Brands .
It uses Deep learning, to build artificial neural networks to mimic the way organic(living) brains sort or process information, applying AI in a number of areas.
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Many data analysis, big data, and machine learning projects require scraping websites to gather the data for further analyze :
“A CDP is a technology that collects data in a governed way from sources like web, mobile, in store, call center, and IoT, unifies it to create accurate customer profiles in real time, then makes it accessible to and actionable for other tools and technology.”
---- The Python programming language is widely used in the data science community, and therefore has an ecosystem of modules and tools : Beautiful Soup module / Selenium / pandas - turn the unstructured data on the web into machine readable, structured data which is ready for analysis ----
While interactive and responsive chart types tools starting as xls / cvs Excel files , transfered to tableau software , range from simple bars and lines to arrow, range and scatter plots , help into creating data analysis, from locator maps to thematic choropleth & symbol maps.
Some good examples of data scrapping / web scraping are: News articles; Sports scores ; Weather forecasts; Stock prices; and Online retailer prices.
Apps in Google Maps with AI-enable mapping search / scans road information, using algorithms to determine the optimal route to take on foot , a car, bike, bus or train. Google Maps
— especially Google Earth are low-level graphics API like WebGL interact with 3D content on a website and mobile devices using JavaScript binding to access the GPU. The WebGL API
— especially shader programming in the Graphics Library Shader Language (GLSL).
App Engine is part of Google Cloud Platform runtime environments for applications,
- one for each of four programming languages: Java, Python, PHP, and Go - designed to host applications with many simultaneous users. An application, written for App Engine, can serve many simultaneous users without
degrading performance, as it scales automatically ; a suite of services for running scalable applications, performing large amounts of computational work, and storing, using,and analyzing large amounts of data - Google Cloud Platform offers several kinds of data storage you can use with an AppEngine app, including a relational database (Google Cloud SQL). Most scalable apps use Google Cloud Datastore, or as it is known to App Engine veterans, simply “the
datastore.”. The features of the platform work together to host applications efficiently and effectively, at minimal cost.
With indexes and optimistic concurrency control, Cloud Datastore is designed forapplications that need to read data quickly, ensure that the data it sees is in a consistent form, and scale the number of users and the size of the data automatically.
App Engine’s specific role on the platform is to host web applications and scale them automatically. Using the other services of the platform as needed, especially for data storage.
Each Google account can own or be a member of up to 25 Cloud projects. A Cloudproject has exactly one App Engine “app,”. A project includes all of the Cloud resources for a major application .
That said, having multiple projects for different purposes is often useful just to keepthings organized. Each project has its own billing configuration and list of contributors. A single company that produces multiple web products might have one projectper product.
If 25 projects per account is a burden in your case, Google offers more apps with theirpaid support programs.
You can create an app by using the free limits without setting up a billing account.
Free apps never incur charges, but are constrained by the free quotas. --- Understand data store models : Generally, it's wiser to start by considering which storage model is best suited for the project requirements: to choose from among SQL and NoSQL databases. Then consider a particular data store within that category, based on factors such as feature set, cost, and ease of management.
Polyglot persistence is used to describe solutions that use a mix of data store technologies.
A datastore is the storage repository for virtual machines and their data. A datastore can be either a NetworkFile System (NFS) or Virtual Machine File System (VMFS).
Cisco UCS Director provides a task library tocreate datastores from physical storage. You can add, delete, and scale clusters.
Therefore, it's important to understand the main storage models and their tradeoffs.
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On a technical level, Google Analytics works through JavaScript tags that run in your website’s source code and is usually operated with Google Tag Manager - – these JavaScript tags running Google Analytics set cookies on their browsers that harvest personal and sometimes sensitive data from them in return.
The question arises : " Is Google Analytics GDPR compliant to use? How do you balance Google Analytics, cookies and end-user consent on your website?" Google Tag Manager is a hugely popular tool for websites of any size and shape. It organizes all third-party tags on your website (like Google Analytics or Facebook pixels), and it also controls when these are triggered. Important for website owners to know, is that almost all of such “third party tags” will set cookies that, according to EU law (the GDPR), fall into categories that require the explicit prior consent of your users.
In other words, tags are what happens, while triggers are when what happens.
Inceptionv3 is a convolutional neural network for assisting in image analysis and object detection, and got its start as a module for
Googlenet
— especially shader programming in the Graphics Library Shader Language (GLSL).
RESEARCH COLLECTION | 2020 : Connect Google Analytics to Google Data Studio
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Besides the platform alternatives such as
Supabase ;
Heroku ;
Netlify ;
Pythonanywhere
;
AWS Amplify ;
Back4app ;
Parse ;
Kinvey ;
Backendless - Some Key Features of Firebase as a platform provided by Google integrates open-source tools in real-time that enable the developers to test Machine Learning components,
launch, analyze and distribute apps or database storage for various platforms such as IoT, iOS, web, and Android without hassle-free scalability - They accelerate app development and scale them easily without investing in infrastructure :
offering some perspectives on Baas ( backend as a service) . It takes care of cloud infrastructure and all the backend needs that lets you develop and deploy faster products, such as Realtime Database, Cloud Firestore, and Authentication.
It also allows hosting and offers API's for machine learning tasks like text recognition, image labelling and so much more.
Nowadays, there are tools like
PlugXR - A Cloud-based Augmented Reality platform without the need of code , that allows developers to create their own face filters, for example the Firebase ML Kit.
With Firebase
- an app dev platform built on the Google Cloud Platform providing services and cross-platform SDKs -
it is possible to detect the positions of eyes, mouth, nose, and contours. Such data can then be used to place a 3D mesh with proper graphics over the camera image.
IoT and M2M ( Machine-to-Machine ) Data Analysis , feature extraction, stratified sampling, data integration, normalization , web scraping, pattern recognition - through open source software environments, such as SQLite and R - are system service system that concurrently satisfy three requirements: massive data analysis, real-time data analysis, and deep data analysis for extract challenges of the future.
As well as they Impulse tools to interact with emerging Tecnologies , including SceneKit, Firebase ML Kit, ARCore, RTDB
Additionally, some technologies aren’t compatible with each other, so it's important to check the existing systems.
In response to
predictive analitics - including big data, data mining, statistical modeling, machine learning and assorted mathematical processes. Organizations use predictive analytics to sift through current and historical data to detect trends and forecast events and conditions that should occur at a specific time, based on supplied parameters - to find and exploit patterns contained within data in order to detect risks and opportunities -
- new tools have emerged, such as # Anonymized data # can provide you with useful insights - into user behavior. GDPR restrictions on the collection and use of personal data mean that many analytics users are asking themselves: " Can I do useful analytics without personal data? - Analytics without personal data – a long history and a promising future - "
In 2015, the open sourced
TensorFlow machine learning and deep learning-focused programming platform , allowed anyone to develop neural
network-based solutions using the same technology they use - were the servers can be segmented and analyzed for content and context and Finding new ways to reduce the latency (
Google Video Intelligence Analyzes Images in Video )
;
AI disruption in TV and Broadcasting revolutionized the Cloud opening up video analytics to new audiences, such as
IBM Research Takes Watson to Hollywood with the First “Cognitive Movie Trailer”
;
Content Discovery and Personalization content , based on user information, preferences, watch history, and context - viewing recommendations based on previously viewed or searched videos;
Ad Targeting / Filtering - uses AI to ensure if content is "safe" and not offensive / filters ads and protect the brands of advertisers / sorts ad priorities or themes / Geo-targeting is
used as a way to restrict ad audience to a certain geographic area or regionally direct message to maximize ad efficacy by location ( zipcode / city or country). ;
Content Clustering and Metadata Building - recognizes images from live or recorded videos can lead to metadata tags or descriptive information of a movie or a program beyond its usual essential attributes (genre, idioms, credit ) : building
Datasets from image recognition , cluster content by context that result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of
high-quality training datasets ;
Voice-assisted Content Search & Playback - personal assistants like Siri and Alexa ;
Content Curation through Audience or Scene Recognition / computer vision - through the use of the camera , determine content according to pre-built assumptions or carefully analyzed audience
data ;
Cognitive analysis - that looks deeply into individual viewer consumption habits or even emotions, and then predict intent, tailor content selection, or even produce unique real-time
content ;
Network Optimization - analyzes available bandwidth and delivering the best balance between video quality and streaming bandwidth ;
Time optimization of codecs, network paths and data transfers, all to minimize the amount of data and time to reach a viewer while ensuring optimum video quality .
So has The
“internet of things” (IoT) , connected cars and
wearable computing (Fitbit, Samsung Gear , Garmin) increased the level of interest and the volume / variety of data -
about what is happening across vast and complex human and machine/device networks - such as wearables ( internet-connected fabrics) , eyewear and smartwatch projects ; pair of sunglasses
that projects holographic icons; smartwatch that has a digital screen but analog hands; temporary tattoo that, when applied to your skin, transforms your body into a living touchpad (concept is similar
to braille); virtual reality controller that lets you pick up objects in digital worlds and feel their weight as you swing them .
In the long run, Wearable computing - technology products ranging home automation , such as smart watches, machinery-gadget sensors, smart shirts, belts, contact lenses,
and more - is the paradigm that entails lightweight, miniature computers that are worn much like clothing such that the user and the computer can interact at any time,
as needed.
— There has been a surge of interest in self-driving cars due to breakthroughs of deep learning - deep neural networks that are trained to perform tasks that typically require human intervention.
CNN’s apply
models to identify patterns and features in images, making them useful in the field of Computer Vision -
such as image classification or image captioning by a simulated car in order to drive the car autonomously where CNN learns features from the images and generates steering predictions allowing the car to drive without a human .
Cars can be connected as well it provides some communication interface and a browser that can access other resources.
The same principle can be applied to
smart watches and other interactive devices that adhere to the same model - connectivity protocol - an interface that allow to interact / communicate with the other devices in the same environment,
as they share storage available for storing and retrieving information.
RESEARCH COLLECTION | 2020 - How to explain in plain English - Machine learning vs. AI vs. deep learning
RESEARCH COLLECTION | SIGGRAPH 2019 VÍDEO - How computer graphics expertise will further the state of the art in machine learning ?
Generally speaking: Computer technology and programming languages are different things. The industry does not move that fast,
trends make it appear that way, but generally, not much in programming changed .
There might be awfull lot of languages, though the concepts are pretty similar :
# Windows 10 Universal? It's C# and XAML, which has been around for ages.
# Cloud services? It's just another name for SOA (Service Oriented Architecture) or SaaS (Software as a Service) and been around for literally decades.
# Android? It's Linux and Java, Linux is a copy of something decades old, and Java has been around forever too.
The actual art of programming revolves around understanding computer architectures and operating systems, writing algorithms managing different data structures, optimizing for performance and stability.
As long as you’ve spent enough time building production code, in at least a couple different programming languages, switching to a new one becomes very common.
All the top software companies, Microsoft, Google, Facebook, etc., have mature codebases measured in millions of lines of code. A new employee, no matter how experienced, will take a while to get familiar enough with the codebase to be productive. They will take even longer to become an expert.
RESEARCH COLLECTION | 2020 : What it’s like to be an Apple WWDC student scholar and why you should apply this year.
REPOSITORY OF SCIENTIFIC RESEARCH PAPERS | 2020: Google Colaboratory.
ACADEMIA | 2020: Microsoft Academic knows journal titles, conference names, and many research topics.
ACADEMIA | 2020: Cursos e certificações Microsoft Academiy .
This means that new players have inserted themselves into the value chain, while hundred billion lines of new software code are added to the existing digital infrastructure of our world.
So, I also personally think that a hybrid solution is an optimal answer in many software-related cases as the web development industry is currently going into a hybrid phase as well, with Server-Side Rendering (SSR) and Incremental Static Generation (ISG) data fetching options ---
"
They solve the problem with pre-rendering the most critical software parts on the server and everything that needs to be asynchronous will be put together in the browser ”(
Szczeciński, B. (2018) 'What's Server Facet Rendering and do I would like it? )
--- .
There is abundance of data in the new digital age, and can be harnessed to gather insights through application of data analytics.
In order to provide oversight and governance over the collection, usage and management of data, it's also necessary to understand where the data is coming from and whether it was properly permissioned.
Systems aren't always identical because clients present different demands over time —whether it's storage, CPU, or database—and these demands change over the lifecycle of the customer’s needs. So systems that can't evolve and scale don't keep up to the speed of technology changes and get stuck to technical difficulties quite often.
More than ever, we are an interconnected world where the actions of one person or device in a social or physical network can have a “butterfly
effect”on all of the people and devices across that Network and On Languages of Interaction ( Physical manipulation; Input using code; Mouse manipulation; Presence, location, and image; Haptic interfaces
and multitouch; Gesture; Voice and speech recognition ).
Alongside a higher cost technology or cryptographic schemes even in face of quantum computing - data infrastructure issues, and ethical challenges on How
lattice-based cryptographic algorithms can be scaled to protect more types of electronic information - ; also, the process of creating games, environments / ads were considered to be
essential scalable, captivating and engaged into clean design , to avoid damage to the user experience - and potentially the brand VR / security . Currently, the high-end tools that exist for XR
creation are complicated and difficult to learn; those without a coding background have more difficult in implementation - the reason why this has added market pressure towards 360 video interactive
content, when the only way to disengage with the ad is to remove the headset. “AR” was coined by Boeing researcher, Tim Caudell in 1990 and comes here in advantage to VR while XR becomes the solution
in between - new value in terms of functionality, reliability, convenience or price ; Imagining ways of New and exciting medium to create unique 3D apps and experiences - shaping the future of art
, it enables new applications on Smartphones, Smart Glasses, City-wide Outdoor localization and tracking : like accurate AR way-finding, visualizing urban points-of-interest, social AR, architecture
pre-visualization and historical restoration.
The design and analysis of geometric algorithms has seen remarkable growth in recent years, due to their application in, for example, computer vision, graphics, virtual reality, medical imaging and CAD.
Onwards — The next era of spatial computing -
the user experience is still a primary obstacle for AR mass adoption and the biggest obstacle for VR mass adoption too; as it is gradually gaining influence on automobile industry - In the future , people will have access to information via glasses, lenses or other mobile devices ; autonomous vehicles, drones and robots move freely environments - understanding where they are; where they are going and what is around them -.
By solving the problem of inaccurate positioning from GPS to camera-enabled Scape’s VPS long term vision, many of the applications once imagined by
AR developers, are now a reality and It's expected to AR revenues surpass VR revenues by 2020 - Knowadays , almost everyone owns a cellphone. Plus, mobile phones have upgraded to the required hardware
for AR technology including CPU, sensors, and GPU - enabling infrastructure for a vast array of new spatial computing services , accelerated by the imminent arrival of widespread 5G networking and edge
compute, delivering massive bandwidth at extremely low latency
.
RESEARCH COLLECTION | 2020 - Web VR Experiments with Google
LEARNED LESSONS | 2020: Estruturas WebXR
TOOLKIT AR | 2020: New Spark AR Studio Integrations Arrive in Blender/ Creators can now build 3D assets and AR experiences more efficiently.
"Customer experience with Digital Content refers to a customer’s perception of their interactive and integrative participation with a brand’s content in any digital media. " - (Judy & Bather, 2019) -
In addition to adding Augmented Reality to the product value, Microsoft has been offering MSOffice applications for its HoloLens device and showing what future offices can look
like without screens and hardware. This could also point to new virtual competitors. AR apps can serve as a further direct-to-consumer channel.
Some unanswered questions that are both theoretically and managerially relevant are: " How does it impact consumer-brand relationships, for instance, if consumers 3D-scan branded products and replicate them as holograms?
How do consumers interact with virtual products in their perceived real world, compared to real products - what advantages and disadvantages do consumers see ? Which dynamic capabilities drive the success of Augmented Reality Marketing? Which competencies do Augmented Reality marketers need? How should these requirements be integrated into digital
marketing curricula to lead for better decisions and lower return rates? How should Augmented Reality Marketing be organized and implemented - How does good content marketing or good storytelling - inspirational user experiences - are organized? What drives the adoption of Augmented Reality?
What advantages and disadvantages do consumers see in virtual versus real products ? How can the success of Augmented Reality Marketing be measured?"
_______________ At the End of the Event I suggested Filipe Barroso
( responsible for organizing the
Lisbon Google Developer Groups Event ) that it would be invaluable to get in touch with programming schools like
ETIC that we all could engage into future
educational workshops together - intersecting areas and interact with the events. For a person who is learning it was important to interconnect: students expressed opened to initiatives that included group
and teamwork contexts - sharing knowledge and opportunities to grow - .
When I spoke to Filipe Barroso, I felt it would be a good initiative for all - to generate revenue and bridging the gap between knowledge seeking and sharing an opportunity for self-discovery and personal development.
Eventually, other initiatives starting with this GOOGLE event spread on the same direction , so web development / media-programming colleagues, brought up a bridge together event # Code in the Dark
- merging different courses in a workshop google event. I felt willing, because it taught me more than
programming skills that any good proggeammer strives, such as coding(20%) ; algorithmic thinking (30%) ; computer science and software engineering concepts (25%) ; languages and software technologies (25%) :
The importance of these Soft skills and proactive initiatives also from others, which I learnt from during this process, was
for me more about "Sharing" in "Effective Interpersonal Relationships": aware that all social movements, are about others, how to learn with each other as a team; co-working towards mutual success and not towards an individual
behaviour. This is what I understand to be the qualities of teamwork and
#the road to create value. When studying programming, soft skills come at use in a practical way - job collective satisfaction beyond a collective co-working perspective range.
Intersecting Personal Experiences - I got to the conclusion that Technology itself continues to evolve creating performance and productivity opportunities for business and even reshape the way we imagine social network as it interacts with the future.
Tech and IT Organizations suffer from constant changes due to hardware evolution - this pushes competition between industry sectors -. ~ That's why I understand the
importance of educational skill upgrades inside tech associations and organizations [ Professional development , through courses or training ]. Skill upgrade should not be ignored if it really wants to make business-market differences.
That is also the main fact why I have pursued knowledge in different Educational systems. In a world of constant transformation,
it is important to stay up to date and try different approaches. You get to a point realizing solution's that disable our ability to grow and innovate will not work to survive.
Even Though, I witnessed a kind of resistance to
CPD - Continuing Professional Development (CPD) – Continuing Education – Some company’s feel threatened or create resistence ( encounter reluctance) - having hard time in understanding on how corrosive This attitude could turn
out to be for every coworkers productivity and creativity: it only retrogrades growth and creates miss understandings or internal conflicts that could be easily solved with Education and shared perspectives.
Training can also become a means of altering behavior, not in a punitive way but so that gaps inorganizational performance can be closed. Redifining the value is not just about profit maximization issues, but sustainable growth towards the measure of value ( Value Creation vs. Revenue Extraction) . The concept of training has many more aspects than just learning a skill:
: Productivity; Quality; Empowerment of intellectual property; Alignment & Teamwork; Liability; Risk reduction; Professional development that supports employees in gaining a wider perspective in theirjobs and in their
personal lives ; evaluates what level of performance will be required to assist the organization inachieving its goals; Establishes a strategy to meet current and future needs; Determines where gaps currently exist
between the existing performance andthe required performance - Preparing for Change through Knowledge Sharing; Business Conduct and Social Responsibility.
The Reduced cost comes with improve quality , for example,
reducing the amount of rework and returns. Similarly, we
reduce cost when we raise productivity or decrease lost time due to accidents.
Just like The best stories have interesting characters that have been put into a difficult situation, I learned with past projects that the path to ensure growth and create value in a business ecosystem is a process that integrates consistent elements - such as , resilient; security / compliance; interoperabile ; flexible scaling : combining with the right tools for the team to grow from a human and professional point of view.
Important tools, that allow development teams to deliver software or other projects at an ever-increasing pace without compromising quality , because sometimes it can be easy to lose oneself in overwhelming routine .
Informed individuals are less likely to panic as they understand what’s going on and how to respond appropriately. They’re more likely to prepare and prevent disasters when they understand the real risks that they
might face
— to improve your security wisely, to maximize the impact, and the metrics you’ll need to make decisions, set goals and track progress. Software designers, developers, and architects are constantly confronted
with the same confounding problem: how to design software that is both flexible and resilient amid change. The more connected, proactive or knowledge sharing, higher the quality exchange between employees and more productive
/ healthy workplaces - .
Why is it so important being organized and have a balanced legal / liable business plan ? Those who own "brick-and-mortar " operations, must understand liability and how it affects them.
Unfortunately, accidents happen all the time. Understanding liability, conducting trainings, getting proper coverage, and other steps can act as a shield against financial claims. As you work to make your business safe
and prevent accidents. If a
client is unhappy with deliverables, timelines, or even
the outcome of the project, he could file a lawsuit based on your management service agreement / contract . Upgrade, migrating knowledge ecosystems will deliver reliable, legal, faster performance to all
staff.
It's also important to put inside the clients skin: Consistency determines rather they decide to stay with contract or walk away towards other services.
"If you're facing error, call it version 1.0 and keep trying! "
When I look back to this event, even though I wasn't totally prepared to understand some concepts, it did make sense later. This is the process of knowledge: to realize that even if something does
not make sense back then in time, it will eventually connect in the Future If one stands firm to his convictions and stays open to opportunities.
LEARNED LESSONS | 2020: Build useful apps, internal tools, simplified workflows, or brilliant bots for just your team or Slack's millions of users.
Since I've already been down this road before, I understand that Technology that supports collective interaction includes online discussion boards and mailing list. The same way as Communication in teams - is equivalent to the neural network of the human body. So even after the google event, I opened a channel online - on our Computer Science
SLACK called "eventos_tech" - the virtual space, where I shared all that I learnt
in group, as an incentive to my colleagues sensibilize towards the importance of exchanging knowledge and being there to help the other - the notion of shared workshops and events on tech , creates or motivates
towards other bigger challenges. It was also important to understand how Thee lack of an adequate project scope to contextualize the project so that it does not become dispersed or mispercept by teamwork members
and even future clients; underestimating the time and effort required to deliver a task can turn a challenging project into a hellish project. Without clarity and vision we’re unfocused, going nowhere fast.
Every person will have his/her own way to learn - their own learning process : a time to absorb information and a time to be able to learn how to decode , inter-connect and re-create ideas - respecting
this is understanding oneself - to be aligned with your consciousness . Change is about alowing transformation of ideas. Reenforce knowledge , comes with consistently learning - Go back to the start - relearn
, and try it out - implement data , sharing experiences ; teaching others after learning it, in a clearer way.
What lacks proper hierarchical structure needed for learning a subject matter thoroughly, because this could lead to your being stuck quite frequently. In short, you will not have the know-how—the comprehensive knowledge—you need to use that language as a tool—. Workshops and interactive educational programs help people understand themselves ; be in contact
with the market; sharing and gripping the right knowledge.
Developers need "soft skills" like the ability to learn new technologies, communicate clearly with management and consulting clients, negotiate a fair hourly rate, and unite teammates and coworkers
- nurturing gratitude - in working toward a common goal.
Throughout the years, I learned not to fear my own opinion, even if others do not understand / disagree
decision making. I don't fear Failure and rather prefer to start from the beginning or unveil "key" strategies, because
I believe in solutions and the capacity of overcome obstacles - Strength and weaknesses - rather, apply the learnings from each experiment in future efforts. Error can
teach us more about a problem that we might not have seen before and prepare to identify risks : by identifying / understanding where the project fails upgrades the impact of effective risk management (Key To
Innovation) on project success. This doesn't mean I keep repeating the same failures all over again, but instead, commit myself to encounter knew challenging ones , so I can learn more throughout the process
of measuring / tracking sequences of keystrokes, that reconfigure awareness networks.