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Customer development is a formal methodology for building startups and new corporate ventures. It is one of the three parts that make up a lean startup (business model design, customer development, agile engineering)
The process assumes that early ventures have untested hypotheses about their business model (who are the customers, what features they want, what channel to use, revenue strategy/pricing tactics, how to get/keep/grow customers, strategic activities needed to deliver the product, internal resources needed, partners needed and costs). Customer development starts with the key idea that there are no facts inside your building so get outside to test them. The hypotheses testing emulates the scientific method – pose a business model hypothesis, design an experiment, get out of the building and test it. Take the data and derive some insight to either (1) Validate the hypothesis, (2) Invalidate the Hypothesis, or (3) Modify the hypothesis.[2][3]
Chaos pilots are people who can creatively lead a project through uncertainty. They have negative capability, but they also have other critical skills, such as the ability to create structure within chaos and take action. Leaders who are chaos pilots are able to drive a team forward on a project even as the environment around them fluctuates.
In the modern context, negative capability can be thought of as the ability to be comfortable with uncertainty, even to entertain it, rather than to become so anxious by its presence that you have to prematurely race to a more certain, yet suboptimal, conclusion. Whereas many people cannot stand the fuzziness of uncertainty, those who demonstrate negative capabilities can facilitate the exploration of new terrain and the discovery of an adjacent possible opportunity.
Just one more thing,…….”
Now, here is the insight that you can capitalize upon: people will often reveal their important information at the end of a conversation.
Great insights appear when people
think that the interaction is over.
Therapists, salespeople, and consumer researchers repeatedly notice this when interviewing people in home visits and focus groups. Don’t relax at the end of a session, be more alert.
You ask the Columbo question to take advantage of the principle that the best information might come at the end of a conversation. The Columbo Question is the last question you ask:
Is there anything that I haven’t asked you that I should have asked you?
Try out the Columbo Question the next time you are searching for information. Here are some examples of useful information that I and others have discovered with the Columbo Question:
Peter Falk’s portrayal of Lt. Columbo made this unassuming-but-determined character a genius at putting people at ease and exploiting the strengths of his own personal style. He brought a sense of curiosity and was sensitive to inconsistencies and incongruities. He wasn’t intimidated by wealthy, powerful, or brilliant people.
Among competing hypotheses, the one with the fewest assumptions should be selected.
The Pirate Funnel is a framework to cut a company in pieces and shows you where to focus your attention. The funnel is developed by Dave McClure and called the Pirate Funnel because the first letters spell out AAARRR for Awareness, Acquisition, Activation, Retention, Referral, Revenue.
The Pirate Funnel is used by growth hackers to find the weakest point of a business which you should focus on.
The AAARRR framework (also referred to as the A3R3-funnel) cuts a company in six steps (Awareness, Acquisition, Activation, Retention, Referral, Revenue). Customers have to flow through each of these steps and, by filling in this framework, you’ll find the gaps in your business.
For example, you might already see that you don’t have enough customers, but what should you do to get more customers/users? Maybe you should do more marketing to reach more people? Or maybe you should optimize your website? Or is it that one feature that you should develop to be more interesting for people?
Well, the Pirate Funnel could help you find this bottleneck. If you follow the steps below and fill in all the numbers, you’ll see what part of your funnel is hurting your customers the most. Therefore you know that this is the part where you get “the biggest bang for your buck”. Every time you improve any step of your Pirate Funnel it will help to improve your ‘North Star Metric‘ and therefore your long-term growth.
Ready to get started with Growth Hacking? Then the Pirate Funnel is your perfect starting point! Let’s get started…
Pepper là một chuỗi tương tự như salt, nhưng khác biệt là ta cần giữ bí mật pepper, lưu ở một chỗ khác ngoài database, và không cần pepper-per-user, chỉ cần 1 pepper là đủ.
Reference: https://xluffy.github.io/post/how-to-hash-store-password/
Like so many words we use commonly, trust has many layers of meaning. While most of us have similar general perspectives about what it means to trust another person, there are some subtle differences in how we view this simple word.
The words I often use to describe the two sides of trust are transactional trust and relational trust, and here is how I define the terms:
At different times and in different situations, both components of trust can come into play in our interactions and relationships with other people. While most people experience and rely upon both trust components as they make decisions about how to interact with others, there are subtle differences in the priority that people place on the two components as they make decisions.
Leaders who focus heavily on task issues often place a higher priority on transactional trust – do people follow-through on commitments and complete tasks – than they do on relational trust. As a result, they can often find ways to stay engaged and working with a person that they do not “like” because they trust that the person will get things done.
Leaders who see the world through a relational filter often place a higher priority on relational trust – do people act in ways that build and protect relationships – than they do on transactional trust. And, they can often stay engaged and working with a person they like even if the other person has challenges with meeting deadlines and completing tasks.
http://recoveringengineer.com/leadership-skills/the-two-sides-of-trust/
Foot-in-the-door (FITD) technique is a compliance tactic that aims at getting a person to agree to a large request by having them agree to a modest request first.[1][2][3]
This technique works by creating a connection between the person asking for a request and the person that is being asked. If a smaller request is granted, then the person who is agreeing feels like they are obligated to keep agreeing to larger requests to stay consistent with the original decision of agreeing. This technique is used in many ways and is a well-researched tactic for getting people to comply with requests. The saying is a reference to a door to door salesman who keeps the door from shutting with his foot, giving the customer no choice but to listen to the sales pitch.[4]
In the foot-in-the-door (FITD) technique smaller requests are asked in order to gain compliance with larger requests, while door-in-the-face (DITF) works in the opposite direction, where larger requests are asked, with the expectation that it will be rejected, in order to gain compliance for smaller requests.
An alternative postulated by Dolinski (2011) is the foot-in-the-face (FITF) technique: compliance is greater when a second request is made immediately after the first is rejected, but after a time lapse of two or three days if the first request is accepted. Researchers found between 63% and 68% compliance rates when using the FITF technique, while traditional techniques showed lower rates of around 50%.
The fight-or-flight response (also known as the acute stress response), refers to a physiological reaction that occurs when we are in the presence of something that is mentally or physically terrifying.
The fight-or-flight response is triggered by the release of hormones that prepare your body to either stay and deal with a threat or to run away to safety.
The fight-or-flight response can be triggered by both real and imaginary threats.
While the fight-or-flight response happens automatically, that doesn't mean that it is always accurate. Sometimes we respond in this way even when there is no real threat. Phobias are good examples of how the fight-or-flight response might be falsely triggered in the face of a perceived threat.
Andy Grove emphasizes that a manager’s most important responsibility is to elicit top performance from his subordinates..
Unfortunately, one management style does not fit all the people in all the scenarios. A fundamental variable to find the best management style is task-relevant maturity (TRM) of the subordinates.
TRM | Effective Management Style |
---|---|
low | structured; task-oriented; detailed-oriented; instruct exactly “what/when/how mode” |
medium | Individual-oriented; support, “mutual-reasoning mode” |
high | goal-oriented; monitoring mode |
A person’s TRM depends on the specific work items. It takes time to improve. When TRM reaches the highest level, the person’s both knowledge-level and motivation are ready for her manager to delegate work.
The key here is to regard any management mode not as either good or bad but rather as effective or not effective.
What is the Base Rate Fallacy?
When provided with both individuating information, which is specific to a certain person or event, and base rate information, which is objective, statistical information, we tend to assign greater value to the specific information and often ignore the base rate information altogether. This is referred to as the base rate fallacy, or base rate neglect.
Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production.
To specifically address the uncertainty of distributed systems at scale, Chaos Engineering can be thought of as the facilitation of experiments to uncover systemic weaknesses. These experiments follow four steps:
CFT is a theory of expertise in ill-structured domains. I first talked about CFT in How Note Taking Can Help You Become an Expert 2. To recap, there are four big ideas in the theory:
An ill-structured domain is a domain where there are concepts, but the way these concepts instantiate in the real world are highly variable.
Because of this variability, cases are more important than concepts when learning in ill-structured domains.
Experts in ill-structured domains reason by combining fragments from previous cases that they’ve seen. In other words, they reason by analogy.
Experts in ill-structured domains have an ‘adaptive worldview’, meaning that they do not think there is one root cause or one framework or one model as explanation for a particular event that they observe in their domain.
What is a PayFac (Payment Facilitator)?
A Payment Facilitator, or PayFac, is a sub-merchant account used by merchant service providers to provide payment processing services to their own clients, known as sub-merchants. A Payment Facilitator or PayFac simplifies merchant account enrollment which allows smaller companies to quickly gain the upper hand. A PayFac will smooth the path to accepting payments for a business just starting out.
During the application process, you need to provide basic information to get started. Once the account is approved, you can start processing payments within hours (as a sub-merchant under the PayFac account). This is quite an attractive timeline. Especially for an SMB where it can take days or even weeks to get an account approved via the traditional channel.
These four by-products is how you get at the tacit knowledge of practitioners
RPD: The Recognition-Primed Decision Making Model
NDM: Naturalistic Decision Making
CTA: Cognitive Task Analysis
Design Thinking is essentially a problem-solving approach specific to design, which involves assessing known aspects of a problem and identifying the more ambiguous or peripheral factors that contribute to the conditions of a problem. This contrasts with a more scientific approach where the concrete and known aspects are tested in order to arrive at a solution. Design Thinking is an iterative process in which knowledge is constantly being questioned and acquired so it can help us redefine a problem in an attempt to identify alternative strategies and solutions that might not be instantly apparent with our initial level of understanding. Design Thinking is often referred to as ‘outside the box thinking’, as designers are attempting to develop new ways of thinking that do not abide by the dominant or more common problem-solving methods – just like artists do. At the heart of Design Thinking is the intention to improve products by analyzing how users interact with them and investigating the conditions in which they operate. Design Thinking offers us a means of digging that bit deeper to uncover ways of improving user experiences.
Source: vexere
As I developed as a CEO, I found three key techniques to be extremely useful in minimizing politics.
Hire people with the right kind of ambition—The cases that I described above might involve people who are ambitious, but not necessarily inherently political. All cases are not like this. The surest way to turn your company into the political equivalent of the US Senate is to hire people with the wrong kind of ambition. As defined by Andy Grove, the right kind of ambition is ambition for the company’s success with the executive’s own success only coming as a by-product of the company’s victory. The wrong kind of ambition is ambition for the executive’s personal success regardless of the company’s outcome.
Build strict processes for potentially political issues and do not deviate—Certain activities attract political behavior. These activities include:
Performance evaluation and compensation
policy.https://docs.microsoft.com/en-us/sql/relational-databases/indexes/create-filtered-indexes?view=sql-server-ver15 filtered index and
https://www.postgresql.org/docs/current/indexes-partial.html partial index
are used to:
Fundamental Attribution Error: We judge others on their personality or fundamental character, but we judge ourselves on the situation.
Self-Serving Bias: Our failures are situational, but our successes are our responsibility.
In-Group Favoritism: We favor people who are in our in-group as opposed to an out-group.
Bandwagon Effect: Ideas, fads and beliefs grow as more people adopt them.
Groupthink: Due to a desire for conformity and harmony in the group, we make irrational decisions, often to minimize conflict.
Halo Effect: If you see a person as having a positive trait, that positive impression will spill over into their other traits. (This also works for negative traits).
Moral Luck: Better moral standing happens due to a positive outcome; worse moral standing happens due to a negative outcome.
False Consensus: We believe more people agree with us than is actually the case.
Curse of Knowledge: Once we know something, we assume everyone else knows it, too.
Spotlight Effect: We overestimate how much people are paying attention to our behavior and appearance.
Availability Heuristic: We rely on immediate examples that come to mind while making judgments.
Defensive Attribution: As a witness who secretly fears being vulnerable to a serious mishap, we will blame the victim less and the attacker more if we relate to the victim.
Just-World Hypothesis: We tend to believe the world is just; therefore, we assume acts of injustice are deserved.
Naïve Realism: We believe that we observe objective reality and that others are irrational, uninformed, or biased.
Naïve Cynicism: We believe that we observe objective reality and that other people have a higher egocentric bias than they actually do in their intentions/actions.
Forer Effect (aka Barnum Effect): We easily attribute our personalities to vague statements, even if they can apply to a wide range of people.
Dunning-Kruger Effect: The less you know, the more confident you are. The more you know, the less confident you are.
Anchoring: We rely heavily on the first information introduced when making decisions.
Automation Bias: We rely on automated systems, sometimes trusting too much in the automated correction of the actually correct decisions.
Google effect (aka Digital Amnesia): We tend to forget information that's easily looked up in search engines.
Reactance: We do the opposite of what we're told, especially when we perceive threats to personal freedoms.
Confirmation Bias: We tend to find and remember information that confirms our perceptions.
Backfire Effect: Disproving evidence sometimes has the unwarranted effect of confirming our beliefs.
Third-Person Effect: We believe that others are more affected by mass media consumption than we ourselves are.
Belief Bias: We judge an argument's strength not by how strongly it supports the conclusion but how plausible the conclusion is in our own minds.
Availability Cascade: Tied to our need for social acceptance, collective beliefs gain more plausibility through public repetition.
Declinism: We tend to romanticize the past and view the future negatively, believing that societies/institutions are by and in large in decline.
Status Quo Bias: We tend to prefer things to stay the same; changes from the baseline are considered to be a loss.
Sunk Cost Fallacy (aka Escalation of Commitment): We invest more in things that have cost us something rather than altering our investments, even if we face negative outcomes.
Gambler's Fallacy: We think future possibilities are affected by past events.
Zero-Risk Bias: We prefer to reduce small risks to zero, even if we can reduce more risk overall with another option.
Framing Effect: We often draw different conclusions from the same information depending on how it's presented.
Stereotyping: We adopt generalized beliefs that members of a group will have certain characteristics, despite not having information about the individual.
Outgroup Homogeneity Bias: We perceive outgroup members as homogeneous and our own ingroups as more diverse.
Authority Bias: We trust and are more often influenced by the opinions of authority figures.
Placebo Effect*: If we believe a treatment will work, it often will have a small physiological effect.
Survivorship bias: We tend to focus on those things that survived a process and overlook ones that failed.
Tachypsychia: Our perceptions of time shift depending on trauma, drug use, and physical exertion.
Law of Triviality (aka "Bike-Shedding"): We give disproportionate weight to trivial issues, often while avoiding more complex issues.
Zeigarnik Effect: We remember incomplete tasks more than completed ones.
IKEA Effect: We place higher value on things we have partially created ourselves.
Ben Franklin Effect: We like doing favors; we are more likely to do another favor for someone if we've already done a favor for them than if we had received a favor from that person.
Bystander Effect: The more other people are around, the less likely we are to help a victim. (though this technically isn't a cognitive bias, it's another important form of bias, according to TitleMax).
Suggestibility: We, especially children, sometimes mistake ideas suggested by a questioner for memories.
False Memory: We mistake imagination for real memories.
Cryptomnesia: We mistake real memories for imagination.
Clustering Illusion: We find patterns and "clusters" in random data.
Pessimism Bias: We sometimes overestimate the likelihood of bad outcomes.
Optimism Bias: We sometimes are over-optimistic about good outcomes.
Blind Spot Bias: We don't think we have bias, and we see it in others more than ourselves.
The bullseye framework follows three simple steps, intending to hit one target: traction!
A feature of a job that will make a worker unhappy if it is not provided.
https://www.mindtools.com/pages/article/herzberg-motivators-hygiene-factors.htm
Product analytics is the process of analyzing how users engage with a product or service. It enables product teams to track, visualize, and analyze user engagement and behavior data. Teams use this data to improve and optimize a product or service.
The JD-R model classifies every occupation into two general categories: job demands and job resources. Job demands are physical, psychological, social or organisational aspects of the job that require effort and come with a cost. These could be long work hours, high work pressure, and demanding interactions with bosses. But these factors are not necessarily negative! Instead, they can become negative if they don’t let up and prevent the employee from getting adequate rest.
As an employee, if you have constant high job demands that never seem to let up, you need to take advantage of the job resources that are available to you.
More specifically, you need to be given autonomy in your job, you need to receive fair and effective feedback, and you should have social support and high-quality relationships with your supervisor. The primary caveat here is that you do not have full control of the job resources available to you, since this is a function of your direct manager, company leadership, and the work environment.
If you are an employer, understand that your employees can have high job demands and not be at risk of burnout if you provide them with high job resources. Build a better work culture that includes more feedback loops, allow employees to work autonomously, and dedicate time to cultivate a high quality relationship with your employees.
TL;DR
Spend less time trying to be brilliant and more time trying to avoid stupidity.
Always operate inside your circle of competence, anything that you do outside your circle of competence is gambling.
When you are weighing alternative hypotheses the one with the fewest necessary assumptions should be chosen.
You have to decide whether you want to have a better today at the cost of tomorrow or a better tomorrow at the cost of today.
Always think about the second-order consequences of your actions, that way you will be able to keep a long-term mindset.
docker run --ipc=host
The ipcMode parameter allows you to configure your containers to share their inter-process communication (IPC) namespace with the other containers in the task, or with the host. The IPC namespace allows containers to communicate directly through shared-memory with other containers running in the same task or host.
Marginal cost refers to the increase or decrease in the cost of producing one more unit or serving one more customer. It is also known as incremental cost.
hello world
Patterns for Patterns
Customer Obsession
Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers.
Ownership
Leaders are owners. They think long term and don’t sacrifice long-term value for short-term results. They act on behalf of the entire company, beyond just their own team. They never say “that’s not my job."
Invent and Simplify
Leaders expect and require innovation and invention from their teams and always find ways to simplify. They are externally aware, look for new ideas from everywhere, and are not limited by “not invented here." As we do new things, we accept that we may be misunderstood for long periods of time.
Are Right, A Lot
Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs.
Learn and Be Curious
Leaders are never done learning and always seek to improve themselves. They are curious about new possibilities and act to explore them.
Hire and Develop the Best
Leaders raise the performance bar with every hire and promotion. They recognize exceptional talent, and willingly move them throughout the organization. Leaders develop leaders and take seriously their role in coaching others. We work on behalf of our people to invent mechanisms for development like Career Choice.
Insist on the Highest Standards
Leaders have relentlessly high standards — many people may think these standards are unreasonably high. Leaders are continually raising the bar and drive their teams to deliver high quality products, services, and processes. Leaders ensure that defects do not get sent down the line and that problems are fixed so they stay fixed.
Think Big
Thinking small is a self-fulfilling prophecy. Leaders create and communicate a bold direction that inspires results. They think differently and look around corners for ways to serve customers.
Bias for Action
Speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk taking.
Frugality
Accomplish more with less. Constraints breed resourcefulness, self-sufficiency, and invention. There are no extra points for growing headcount, budget size, or fixed expense.
Earn Trust
Leaders listen attentively, speak candidly, and treat others respectfully. They are vocally self-critical, even when doing so is awkward or embarrassing. Leaders do not believe their or their team’s body odor smells of perfume. They benchmark themselves and their teams against the best.
Dive Deep
Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdote differ. No task is beneath them.
Have Backbone; Disagree and Commit
Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting. Leaders have conviction and are tenacious. They do not compromise for the sake of social cohesion. Once a decision is determined, they commit wholly.
Deliver Results
Leaders focus on the key inputs for their business and deliver them with the right quality and in a timely fashion. Despite setbacks, they rise to the occasion and never settle.
What Is the Prospect Theory?
Prospect theory assumes that losses and gains are valued differently, and thus individuals make decisions based on perceived gains instead of perceived losses. Also known as the "loss-aversion" theory, the general concept is that if two choices are put before an individual, both equal, with one presented in terms of potential gains and the other in terms of possible losses, the former option will be chosen.
KEY TAKEAWAYS
The prospect theory says that investors value gains and losses differently, placing more weight on perceived gains versus perceived losses.
An investor presented with a choice, both equal, will choose the one presented in terms of potential gains.
Prospect theory is also known as the loss-aversion theory.
The prospect theory is part of behavioral economics, suggesting investors chose perceived gains because losses cause a greater emotional impact.
The certainty effect says individuals prefer certain outcomes over probable ones, while the isolation effect says individuals cancel out similar information when making a decision.
https://www.investopedia.com/terms/p/prospecttheory.asp
https://swagitda.com/blog/posts/when-prospect-theory-meets-chaos-engineering/
Feature engineering is the process of using domain knowledge to extract features (characteristics, properties, attributes) from raw data.
The feature engineering process is:
There is no one-size-fit-all strategy to promote creativity. But our study suggests that leaders should assess how many specialists and generalists they have on their teams. If the pace of change is slow, teams will likely benefit from employing generalists, who can challenge the industry’s taken-for-granted assumptions and bring in new ideas. If the pace of change is rapid, teams will benefit from specialists, who are more likely to help the team innovate.
The goal of MLOps is to reduce technical friction to get the model from an idea into production in the shortest possible time to market with as little risk as possible.
MLOps (machine learning operations) is a practice that aims to make developing and maintaining production machine learning seamless and efficient. While MLOps is relatively nascent, the data science community generally agrees that it’s an umbrella term for best practices and guiding principles around machine learning – not a single technical solution.
Machine learning should be collaborative.
When approached from the perspective of a model – or even ML code, machine learning cannot be developed truly collaboratively as most of what makes the model is hidden. MLOps encourages teams to make everything that goes into producing a machine learning model visible – from data extraction to model deployment and monitoring. Turning tacit knowledge into code makes machine learning collaborative.
Machine learning should be reproducible.
Data scientists should be able to audit and reproduce every production model. In software development, version control for code is standard, but machine learning requires more than that. Most importantly, it means versioning data as well as parameters and metadata. Storing all model training related artifacts ensures that models can always be reproduced.
Machine learning should be continuous.
A machine learning model is temporary. The lifecycle of a trained model depends entirely on the use-case and how dynamic the underlying data is. Building a fully automatic, self-healing system may have diminishing returns based on your use-case, but machine learning should be thought of as a continuous process and as such, retraining a model should be as close to effortless as possible.
Machine learning should be tested & monitored.
Testing and monitoring are part of engineering practices, and machine learning should be no different. In the machine learning context, the meaning of performance is not only focused on technical performance (such as latency) but, more importantly, predictive performance. MLOps best practices encourage making expected behavior visible and to set standards that models should adhere to, rather than rely on a gut feeling.
As mentioned before, MLOps is not dependent on a single technology or platform. However, technologies play a significant role in practical implementations of MLOps, similarly to how adopting Scrum often culminates in setting up and onboarding the whole team to e.g. JIRA. Therefore, the project to rethink machine learning from an operational perspective is often about adopting the guiding principles and making decisions on infrastructure that will support the organization going forward.
According to Martin Fowler Active Directory is:
An object that wraps a row in a database table or view, encapsulates the database access, and adds domain logic on that data. Object carries both data and behavior.
From wikipedia:
A Data Mapper is a Data Access Layer that performs bidirectional transfer of data between a persistent data store (often a relational database) and an in-memory data representation (the domain layer). The goal of the pattern is to keep the in-memory representation and the persistent data store independent of each other and the data mapper itself.
So I like this by Martin Fowler:
The Data Mapper is a layer of software that separates the in-memory objects from the database. Its responsibility is to transfer data between the two and also to isolate them from each other.
Source
https://www.investopedia.com/terms/g/gross-merchandise-value.asp
Assertive inquiry is far more persuasive than simple advocacy, as anyone who’s sat through product arguments at a startup can attest. Once you go from trying to prove that you’re right, to trying to figure out the right answer regardless of the source, you can accomplish far more, and with far less conflict.
We can summarize the flow of data through a Redux app with this diagram. It represents how:
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.