Jack  C

Jack C

1640766600

Tokenomics Explained | Everything You Need To Know

Nowadays, a lot of projects are popping up within the blockchain industry, claiming to be the next big innovation that will change the world. In reality, only a minority is really disruptive. Because of the innovative character of this technology, the number of used cases is unlimited: tracking ownership, the provenance of documents, supply chain management, insurance, and so on. 

In this video, I’ll introduce you to an important concept of tokenomics, or token economics. This new paradigm is shaking the traditional economy, but it includes many challenges. I’ll underline its key concepts, and its main pain points to keep in mind during the creation of a new token ecosystem.

Video Walkthrough,
0:00 Introduction
0:13 What is Tokenomics Explained
1:14 What is Token in Blockchain
2:07 Token vs Cryptocurrency Explained
2:33 Types of Crypto Tokens
2:29 Layer 1 vs Layer 2 Token
4:09 Original Chain vs Forked Chain | Blockchain Forking
4:43 Utility vs Security Token
5:55 Fungible vs Non fungible Token
7:19 What makes Crypto Tokenomics So Different
8:02 Applications of Token Economics Explained
9:45 Investor's Take on Tokenomics Crypto
10:45 Conclusion

#bitcoin #tokens 

What is GEEK

Buddha Community

Tokenomics Explained | Everything You Need To Know
Ian  Robinson

Ian Robinson

1624434540

Everything You Need to Know about Apache Storm

The ever-increasing growth in the production and analytics of Big Data keeps presenting new challenges, and the data scientists and programmers gracefully take it in their stride – by constantly improving the applications developed by them. One such problem was that of real-time streaming. Real-time data holds extremely high value for businesses, but it has a time-window after which it loses its value – an expiry date, if you will. If the value of this real-time data is not realised within the window, no usable information can be extracted from it. This real-time data comes in quickly and continuously, therefore the term “Streaming”.

Analytics of this real-time data can help you stay updated on what’s happening right now, such as the number of people reading your blog post, or the number of people visiting your Facebook page. Although it might sound like just a “nice-to-have” feature, in practice, It is essential. Imagine you’re a part of an Ad Agency performing real-time analytics on your ad-campaigns – that the client paid heavily for. Real-time analytics can keep you posted on how is your Ad performing in the market, how the users are responding to it, and other things of that nature. Quite an essential tool if you think of it this way, right?

Looking at the value that real-time data holds, organisations started coming up with various real-time data analytics tools. In this article, we’ll be talking about one of those – Apache Storm. We’ll look at what it is, the architecture of a typical storm application, it’s core components (also known as abstractions), and its real life-use cases.

Let’s go!

Table of Contents

#big data #data #technical skills #technology #everything you need to know about apache storm #apache storm

David mr

David mr

1624305600

SAFEMOON UPDATE - ALL YOU NEED TO KNOW ABOUT SAFEMOON AND SAFEMOON PREDICTION

SAFEMOON UPDATE - ALL YOU NEED TO KNOW ABOUT SAFEMOON AND SAFEMOON PREDICTION

This is all you need to know about safemoon and I provide my safemoon prediction. This is a huge safemoon update so make sure to watch this video until the end.
📺 The video in this post was made by Josh’s Finance
The origin of the article: https://www.youtube.com/watch?v=ZtX7ZIVcXH4
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
Cryptocurrency trading is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money
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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#bitcoin #blockchain #safemoon #safemoon #all you need to know about safemoon and safemoon prediction #safemoon update - all you need to know about safemoon and safemoon prediction

Jack  C

Jack C

1640766600

Tokenomics Explained | Everything You Need To Know

Nowadays, a lot of projects are popping up within the blockchain industry, claiming to be the next big innovation that will change the world. In reality, only a minority is really disruptive. Because of the innovative character of this technology, the number of used cases is unlimited: tracking ownership, the provenance of documents, supply chain management, insurance, and so on. 

In this video, I’ll introduce you to an important concept of tokenomics, or token economics. This new paradigm is shaking the traditional economy, but it includes many challenges. I’ll underline its key concepts, and its main pain points to keep in mind during the creation of a new token ecosystem.

Video Walkthrough,
0:00 Introduction
0:13 What is Tokenomics Explained
1:14 What is Token in Blockchain
2:07 Token vs Cryptocurrency Explained
2:33 Types of Crypto Tokens
2:29 Layer 1 vs Layer 2 Token
4:09 Original Chain vs Forked Chain | Blockchain Forking
4:43 Utility vs Security Token
5:55 Fungible vs Non fungible Token
7:19 What makes Crypto Tokenomics So Different
8:02 Applications of Token Economics Explained
9:45 Investor's Take on Tokenomics Crypto
10:45 Conclusion

#bitcoin #tokens 

Explaining the Explainable AI: A 2-Stage Approach

As artificial intelligence (AI) models, especially those using deep learning, have gained prominence over the last eight or so years [8], they are now significantly impacting society, ranging from loan decisions to self-driving cars. Inherently though, a majority of these models are opaque, and hence following their recommendations blindly in human critical applications can raise issues such as fairness, safety, reliability, along with many others. This has led to the emergence of a subfield in AI called explainable AI (XAI) [7]. XAI is primarily concerned with understanding or interpreting the decisions made by these opaque or black-box models so that one can appropriate trust, and in some cases, have even better performance through human-machine collaboration [5].

While there are multiple views on what XAI is [12] and how explainability can be formalized [4, 6], it is still unclear as to what XAI truly is and why it is hard to formalize mathematically. The reason for this lack of clarity is that not only must the model and/or data be considered but also the final consumer of the explanation. Most XAI methods [11, 9, 3], given this intermingled view, try to meet all these requirements at the same time. For example, many methods try to identify a sparse set of features that replicate the decision of the model. The sparsity is a proxy for the consumer’s mental model. An important question asks whether we can disentangle the steps that XAI methods are trying to accomplish? This may help us better understand the truly challenging parts as well as the simpler parts of XAI, not to mention it may motivate different types of methods.

Two-Stages of XAI

We conjecture that the XAI process can be broadly disentangled into two parts, as depicted in Figure 1. The first part is uncovering what is truly happening in the model that we want to understand, while the second part is about conveying that information to the user in a consumable way. The first part is relatively easy to formalize as it mainly deals with analyzing how well a simple proxy model might generalize either locally or globally with respect to (w.r.t.) data that is generated using the black-box model. Rather than having generalization guarantees w.r.t. the underlying distribution, we now want them w.r.t. the (conditional) output distribution of the model. Once we have some way of figuring out what is truly important, a second step is to communicate this information. This second part is much less clear as we do not have an objective way of characterizing an individual’s mind. This part, we believe, is what makes explainability as a whole so challenging to formalize. A mainstay for a lot of XAI research over the last year or so has been to conduct user studies to evaluate new XAI methods.

#overviews #ai #explainability #explainable ai #xai

Norvergence - AI for Climate Change: All you Need to Know

AI is available in our lives in numerous spaces, from telephones where we can go without much of stretch access practically any data anyplace on the planet to grocery stores where we can shop with a ‘tick’; from banks where we can undoubtedly handle exchanges online to social stages where we invest the majority of our energy.

Yet, can artificial intelligence make a positive commitment to understanding the issues brought about by environmental change and problems continuously transforming into an emergency?

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Indeed, AI can help environment analysts discover arrangements in numerous spaces, for example, air contamination. An illustration of this is IBM’s Green Horizon Project, which predicts contamination by breaking down ecological information and testing what will occur if contamination is decreased.

Similarly, Google has reduced its server farms’ energy by around 15% by utilizing data from AI calculations.

Projects like these can likewise help and urge different firms to diminish their carbon impression.

Astounding advancement has been made to utilize AI calculations dependent on information from other outrageous climate occasions to recognize hurricanes and environmental waterways. What’s more, even though machines are not entirely believed, environment researchers can work with them to gain better headway.

Also read more related this post visit here

#norvergence #ai for climate change #ai #climate change #all you need to know