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Xtime helps dealers get more vehicles through the service lane in less time to maximize the opportunity of every RO by boosting technician and advisor efficiency — creating superior consumer service experiences and additional dealership revenue. With easy-to-use technology and industry experts, Xtime unlocks the power of service teams and builds consumer trust and dealership transparency, so dealers make more money. Through efficiency, convenience, and trust, Xtime facilitates more than ten million service appointments monthly. Xtime is part of a powerful set of solutions from Cox Automotive that help your marketing, sales, service, and operations workflows stay in sync.

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Solving Time Series Forecasting Problems: Principles and Techniques

Many people have discovered ChatGPT’s competencies in code generation. But, how well does it actually perform, and are there alternatives? In this post, I take a look at some scenarios where AI can and the degree to which it can be useful. Finally, I do my best to evaluate its performance. help with coding Intro ChatGPT has been everywhere in the last few months. Reading and hearing about how people use it and ‘force’ it to make mistakes has been fun for a week or two, but it's getting tiring. For some reason, my LinkedIn feed still has at least one "Look how ChatGPT failed"-post every day, and I don't know what people are trying to prove with that. At the same time, I am perplexed by software developers claiming that they are using ChatGPT to do their work. Statements like "This week, I didn't write a single line of code and only used ChatGPT" even made it to podcasts where people discussed which jobs AI might replace in the future. For everyone who has seriously worked as a software developer, it is evident that AI cannot replace software developers soon. Yes, ChatGPT can generate code for a given problem description, but it is not good at solving problems, which is the main task of a software engineer. AI can support specific tasks, though, and I am looking at some examples in this post. AI Pair Programming Several services implement smart code completion, also called AI pair programming. The term is quite misleading and was probably invented by someone without much experience with pair programming. While pair programming is specifically beneficial when two people work together to discuss how something should be implemented, AI [pair programming](https://Pair programming - Wikipedia  Wikipedia https://en.wikipedia.org › wiki › Pair_programming) tools instead help with the next step. As soon as you decide what to implement and where to put the code, it suggests a solution. The two most popular ones are and GitHub Copilot is based on , a model for translating natural language to code based on GPT-3. According to a paper by OpenAI researchers, the model generated working code for given Python docstrings for more than 70% of the attempts. That's quite impressive but still also emphasizes that it requires basic coding skills (i.e., writing a docstring) to retrieve good results. Like ChatGPT, CodeX can also be used for free. GitHub Copilot Tabnine. OpenAI Codex on the OpenAI website I have used Copilot for private projects for quite a while and liked it a lot. In the beginning (when it was still in technical preview), it mainly copied lines from GitHub code. Since then, it has improved and evolved a lot. Especially for code that implements generic tasks (like calculations or conversions), there is a high chance that Copilot suggests a complete function based on a doc string. For example, when you write it would suggest the complete function, including a return value. def reverse(self, x:int) -> int... Copilot also works well for writing tests. Just add the name "test" to a given function name and it does the job. In contrast, Tabnine was a massive disappointment for me, though, and felt like a dumb auto-completion suggesting mostly useless or wrong code. While Copilot uses one large model, Tabnine is based on several smaller models that solve individual problems. This is probably also why it is more convenient to use Tabnine in local mode and train it with your own code (which is not possible with Copilot). Even with a lot of context and well-named variables, the suggestions I received from Tabnine were often far from what you would expect. Using local mode, it worked well in large repositories with a lot of similar code. But this is far too easy compared to the problems I would expect such a model to solve. It was not smart but felt more like a tool for automatic copy and pasting. There might be other use cases and circumstances where Tabnine works well (for example, in huge company code bases where everything is written in a similar style and language) but as someone who is working on many smaller projects, it just didn't work for me. Asking AI to write Code As mentioned in the intro, one of the primary use cases of ChatGPT seems to be code generation. Of course, that was already possible with CodeX, but the boom of ChatGPT made many more people aware of what is possible. Compared to the plugins mentioned before, this approach aims to translate textual problem descriptions into code instead of being integrated into an existing code base. Doing this task is challenging for a model as it involves understanding a problem and generating suitable, functional code that solves this problem. In the past, many models failed to do the former reliably, and even with more specialized models, it still is a considerable challenge that is not solved by ChatGPT. However, let's have a look at the code ChatGPT generates. Asking ChatGPT to generate a weather app I asked ChatGPT to write a Streamlit application that fetches weather data for Dortmund from a free API and displays it in a chart. This is what I got: import streamlit as st
import requests
import pandas as pd
import plotly.express as px

# Set up OpenWeatherMap API key
api_key = "YOUR_API_KEY_HERE"

# Define function to get weather data from OpenWeatherMap API
def get_weather_data():
    url = f"https://api.openweathermap.org/data/2.5/onecall?lat=51.5134&lon=7.4814&exclude=hourly,minutely&appid={api_key}&units=metric"
    response = requests.get(url)
    data = response.json()
    return data

# Get weather data
data = get_weather_data()

# Convert weather data to a Pandas DataFrame
df = pd.DataFrame(data["daily"])

# Format the date column
df["dt"] = pd.to_datetime(df["dt"], unit="s")
df["date"] = df["dt"].dt.date
df = df.set_index("date")

# Create a line chart using Plotly Express
chart = px.line(df, x=df.index, y="temp.day", title="Dortmund Weather Forecast")
chart.update_xaxes(title="Date")
chart.update_yaxes(title="Temperature (°C)")

# Display the chart in the Streamlit app
st.plotly_chart(chart) In general, that's not too bad. ChatGPT also gave some instructions on how to get the API key. Unfortunately, it didn't tell me I also have to install , but as I asked for a Streamlit app, it's OK to assume I know how to install libraries. plotly Nevertheless, there are two issues: The temperature value is not parsed correctly. It is saved as a dictionary and accessing it with will throw an error. A quick and easy fix would be to replace this with . I assume that's a good example of how the model has learned a lot of different ways how to handle the reply of the API but isn't successful in drawing a connection between parsing the data and accessing it for the chart again. y="temp.day" y=df['temp'].str['day'] The app only works if there is a valid API key and throws an error if there is none. The missing error handling is unfortunate as it displays error messages in the front end. However, it could quickly be fixed by either catching the error and displaying a more user-friendly error message (preferred) or implementing the API call so that the error is not displayed in the UI. Apart from these issues, the code looks fine and runs after fixing the first issue. Also, while the number of comments might be too ambitious in general, it's helpful to understand the generated code. Writing tests with ChatGPT Next, I asked ChatGPT to write a unit test for the application. import unittest
from app import get_weather_data

class TestWeatherApp(unittest.TestCase):

    def test_weather_data(self):
        # Call the function to get weather data
        data = get_weather_data()

        # Check that the data contains the expected keys
        self.assertIn("current", data)
        self.assertIn("hourly", data)
        self.assertIn("daily", data)

        # Check that the daily data contains the expected keys
        daily_data = data["daily"][0]
        self.assertIn("dt", daily_data)
        self.assertIn("temp", daily_data)
        self.assertIn("feels_like", daily_data)
        self.assertIn("pressure", daily_data)
        self.assertIn("humidity", daily_data)
        self.assertIn("dew_point", daily_data)
        self.assertIn("wind_speed", daily_data)
        self.assertIn("wind_deg", daily_data)
        self.assertIn("weather", daily_data)
        self.assertIn("clouds", daily_data)
        self.assertIn("pop", daily_data)
        self.assertIn("uvi", daily_data) This one is interesting. First of all, the test calls get_weather_data(), but the API key is defined outside the function. Therefore, it will run without an API key and will always fail. So the test is useless. Apart from that, this is not a unit test but an integration test. It tests if the (external) API returns the correct data. To implement a unit test, expected data should be mocked, so I asked ChatGPT to fix this. This is not a unit test but an integration test. Can you fix this? import unittest
from unittest.mock import patch
from app import get_weather_data

class TestWeatherApp(unittest.TestCase):

    @patch('requests.get')
    def test_get_weather_data(self, mock_get):
        # Set up test data
        expected_data = {'daily': [
            {'dt': 1645808400,
            'temp': {'day': 5.5, 'min': 2.15, 'max': 7.9, 'night': 3.4, 'eve': 7.9, 'morn': 2.15},
            'feels_like': {'day': 0.3, 'night': -3.04, 'eve': 4.06, 'morn': -4.01},
            'pressure': 1028, 'humidity': 51, 'dew_point': -2.57, 'wind_speed': 2.81, 'wind_deg': 194,
            'weather': [{'id': 801, 'main': 'Clouds', 'description': 'few clouds', 'icon': '02d'}],
            'clouds': 16, 'pop': 0, 'uvi': 2.21}],
            'timezone_offset': 3600}

        # Set up mock response from requests.get
        mock_response = type(
                'MockResponse',
                (object,),
                {'json': lambda self: expected_data}
            )
        mock_get.return_value = mock_response

        # Call the function to get weather data
        data = get_weather_data()

        # Check that the function returns the expected data
        self.assertEqual(data, expected_data) This looks much better, but still, I am missing testing for potential error cases, so I asked again: Shouldn't the unittest also check if the app crashes in case something unusual happens. For example, if the API is down? ChatGPT added this part to the code generated earlier: @patch('requests.get')
    def test_get_weather_data_error(self, mock_get):
        # Set up mock response from requests.get to raise an exception
        mock_get.side_effect = Exception("Connection error")

        # Call the function to get weather data
        with self.assertRaises(Exception):
            data = get_weather_data() This addition looks reasonable. However, as the original app does not handle any error cases, this test doesn't make much sense. Testing if the app doesn't crash when we know it will crash leads nowhere, so I stopped asking. Overall, the results presented by ChatGPT were OK. They certainly help with prototyping or giving a template to start from. However, the code still needs to be made production-ready. ChatGPT would certainly help with that, but improving the code step by step by asking the right questions is not an efficient way of working. Outlook Last year, Deepmind's AlphaCode took part in competitive programming contests and The code and some comments by a human competitor can be found . This has been quite a breakthrough as it was the first time an AI coding model proved problem-solving skills. It will be interesting to see how these models improve and find their way into software development. performed like a median human competitor. here Also published . here

The Current Reality and Future Possibilities of AI-Powered Coding

A Q&A with t2 CEO & Founder, Mengyao Han All you need to know about , the new protocol and social platform for content curation designed to fundamentally change the way we value time spent on reading. t2 What is t2? t2 (time²) is a online publisher built to capture users’ passive contributions like time and attention as they engage with content. decentralized The decentralized platform not only allows users to own the content and its curation, but also the value and knowledge it generates. However, even more revolutionary, it empowers users to take ownership of their attention and accumulate culture as public goods. So this is an application geared for Web3? With the introduction of diverse token incentives that are driving the space and its economy, the new era of the internet is slowly but surely blending the long-established concepts of work and leisure. These two, often polarized domains tend to clash – competing for one of the most precious resources known to man – time. Web3 On t2, time serves as a matrix of value capture and distribution. By monetizing time, the protocol enables users to earn TXT (time x time) tokens, which can be reinvested on the platform or exchanged for real-world goods and services. Built to turn time and attention into discernible and distributable value, t2’s technology passively rewards users to simply read, learn and explore. So you are essentially gamifying reading with t2? We are incentivizing deep reading, since the global reduced attention span is a societal problem. Also the current creator's economy is quite broken. How to align the incentives between readers, writers and curators, t2 has a unique answer by capturing the most bottom-up passive contribution: our attention itself. By capturing the curation value from users’ attention, the platform is poised to drive both the content quality and the growth of t2 communities. Meanwhile, by incentivizing reading, the protocol ushers a reinforced feedback loop created to drive the growth of the content and knowledge markets. Being a decentralized, community-driven social platform, t2 establishes an ecosystem in which all users, including writers, readers, and curators, play an integral part in curating the content, reaping fair rewards for their contribution. The time a user spends reading t2 articles on-chain, tokens are minted and dispersed to the content creator, the reader, and the community. On t2, readers own the value of their engagement and creativity, to depart from Web2’s subscription model, which defined them as consumers, and their attention as a commodity. How is the content curated? On t2 content is curated by different communities, and users can participate in this open curation within their own group. So t2 does not purely rely on the social graph which tends to enclose the user inside his/her own friend circle blinding them from world-class high-quality content, nor rely on the algorithmic recommendations only which are efficient but make us emotionally abandoned. In t2 content curation is bringing both world-class content, and the sentimental value from our social connectivity. To curate the content, community members coordinate within their domains called “territories” through voting and fostering their community’s culture. On the t2 platform, each territory acts as a DAO. To join a territory, you simply stake some native tokens then you become productive inside as a member. You can choose which territories to allocate your productivity, simply by staking or unstaking within different territories with a minimal swap fee, and your reward is highly oriented around what you do inside intead of what you own. If you wish to engage further, you simply lock your territory tokens for a fixed time and become a territory curator, then additional rewards will be given to you based on the territory's curation results. Content creators submit articles to territories to be syndicated. As the attention attracted by the content grows, the value generated for readers, writers, and communities increases. The newly minted token from the listed content then gets split between the creator, territory readers, curators, and the community. Finally, the articles which has accumulated the highest amount of reading time, will become territory artifacts and serve as the public goods of the culture, all happening on-chain curated by human attention alone. Seems t2 is oriented around readers, what about writers? What’s their journey on t2? Without high-quality content, there will be no deep reading in the first place. They are on t2 for several reasons: Own their work, get paid fairly, expand their audience, and connect with their readers and each other. By listing their content inside territories, they get more eyeball value and this can help their work to grow based on the quality, not how many followers they have. Do you see this as the future of decentralized publishing? We are making a great effort to define our own future in publishing. The returned value is based on users' real engagement and collaboration instead of centralized opaque algorithms. Also t2 is the first mover valuing the attention and human effort itself instead of monetizing content with speculations. Also as a publisher, t2 extends its mission from only delivering the content, but also to make reading sexy again, bring people together, empathize how difficult and valuable reading and writing is, and eventually help us regain our attention back and enjoy a better life. Beyond the same incentives, t2 connects different users, whether they are reading, curating, or writing to earn–through shared taste, cultural interests, and topic expertise – creating a fertile soil for decentralized content communities to form, grow, and nurture their own subcultures. On the t2 platform, each territory acts as a DAO. And the territories function as the reputable content houses creators can collaborate with, to reach for a broader audience, with additional curation from the territory curators backing their work. Territories cultivate their own internal cultures by focusing on specific curation themes and setting territory-specific sub-rules–including which content is relevant and what constitutes acceptable behaviour. By utilizing this conduct enforcement model, t2 enables territories to police themselves, while giving high-effort members an additional token incentive and the performance of the territory reflects the subculture's overall value. Users can easily see the horizontal landscape of the social interests, and make their own choices what's the best way of spending their attention. So, this is Web3’s way of deep reading? Most people agree on the inherent values of reading. Even so, developing a reading habit is an investment–of both time and attention. Not finding the time and the convenience of indulging in less attention-grabbing formats, such as podcasts and videos, are among people's top most common excuses for not reading. At t2 we have built a platform that empathizes the difficulty, assists us with distraction-free reading experiences, and allows users to enjoy tangible returns. Web2 changed our lives in ways we never thought possible. It connected us and allowed us to communicate, learn and share like never before. At a high price–making it impossible for us to maintain ownership of our own data, attention, and contributed network value. t2 resolves those issues with web3 technologies and translates users’ subjective and passive contributions into tangible social values–promoting not only beneficial engagements but also long-term individual liberalization. I believe all good things in life come from deep relationships. t2 helps us in deep reading and rewards us for doing the difficult but right things. If t2 can make the world value deep reading more and bring more peace and joy, that’ll be a great thing to witness. What is your ultimate vision for building t2? https://twitter.com/mengyao_han https://twitter.com/t2wrld

It’s Time to Reap the Rewards for Reading in Web3

Tom Brady will go down as one of the greatest football players of all time. Love him or hate him; there is zero doubt about that. His achievements are legendary. He blew past milestones people never thought were possible (and setting records) one can only hope to see broken in their lifetime. One of the essential qualities to Tom Brady’s game is —his leadership has taken him to the biggest stages in the country, getting the maximum talent and productivity out of his teams for the longest time. And while you may not be married to a supermodel or have Tom Brady’s arm, the GOAT can teach us valuable lessons on leadership that we can apply to our own lives. But to understand his lessons on leadership, we must first understand what kind of leader Tom Brady is. his leadership skills What kind of leader is Tom Brady? Brady is best known for . His work ethic and dedication to the game are evident for his teammates to see.  He embodies self-determination, self-discipline, and self-regulation. Unlike many stars in the league, Brady started his NFL career as a 6th round draft pick, virtually condemning him never to make it big. However, because of his hard work, belief in himself, and passion for the game, he remained ready for any opportunity at any time. When starting quarterback Drew Bledsoe was injured at the start of the New England Patriots’ 2001 season, Brady was prepared to step up to the plate (wrong sport, but the analogy works). leading by example Being drafted late may have been a blessing in disguise for Brady’s career—he is one of the few players to have experienced what it’s like a player starting at the bottom and working at the league's highest levels. He leaves the impression that his status is achievable, but shows others through his actions why he is the best. For those around him, Brady exists as the epitome of a success story, from a bottom pick to the greatest to ever play the game. Through his story, he has shown that hard work can genuinely create paths to success. Brady has gained a reputation of being remarkably consistent, constantly training, learning from his mistakes, and performing at a constant level. He has never been known for his athleticism like other elite NFL players; it’s one of the primary reasons he was such a late draft selection. While he has never been able to become the most athletic player in his career, Brady has undoubtedly been able to compensate and minimize his flaws through hard work and relentless focus. He isn’t the fastest player; however, he has developed an elite level of awareness that helps him avoid the defense. By working on his flaws to become a well-rounded player, Tom Brady has been able to find success. What’s remarkable is that Tom Brady has been able to impart this success on others. Using himself as his best example, he shows others what it takes to be the greatest player of all time. That leadership by example is magnified by the fact that he was overlooked at the top of the draft. His dedication and focus got him to the top of the game, and that’s inspiring for his teammates. It brings out the best in those around him as they focus on a singular goal. The idea of leading by example is not exclusive to football, of course. Leading a team in business or leading a team in football requires the same skill set. Leading by example is an excellent way to prove your legitimacy and dedication to others. One common misconception about leading by example is that the leaders are silent, mind their own business, and are generally unapproachable. However, from the told by other players about Brady, he is . Even though he is the first in the facility and last to leave every day, Brady always engages with others, talking to them and coaching them. He leaves the impression that his status is achievable but shows others why he is the best through his actions. This idea can be applied to more mundane work as well. Leading by example is not about leaving your team in awe of your work and achievements; instead, it is about showing that your high level of work ethic is possible and achievable for others. Delivering results underlines what you can achieve with his level of dedication. stories far from a silent leader Brady is also known amongst players for . When with his team, he is both personal and personable. There is no ego to deal with, despite his rarified stature. He understands the winning culture and what it takes to achieve great things at the highest level and under tremendous pressure – and in his case, physical pain. keeping a positive yet competitive team environment Because of this, Brady becomes the biggest supporter of his teammates. He understands that while he may be an outstanding player, football is a team sport, and everyone has a role to play. Brady is motivated to teach others what it takes to win, even in his position. He exemplifies this by becoming a second coach, making adjustments to improve the play, and reassuring each player they have what it takes to be a winner. His winning pedigree backs up his advice: he commands the players' full attention in the locker room. On a personal level, Brady to younger players, showing the areas of improvement while also taking the time to train them and answer any questions they may have. So long as the players are willing to get better, Brady is committed to teaching them what he knows – and those players know that Tom Brady has elevated his status in the league from a backup to an x-time world champ. They want to eat whatever Tom is eating. acts as a mentor Brady also exemplifies outstanding leadership by . , Brady went the extra mile to reward his long-time teammate Rob Gronkowski. Despite the resistance from his coaches, Brady opted to stay in a blowout game to throw an extra pass to Gronkowski, netting him a $500,000 bonus for achieving his completion goal. It’s a perfect example of listening to your teammates, understanding what they want, achieving their goals together, and rewarding them for their effort. aligning personal and team objectives for more established players During his tenure on the Tampa Bay Buccaneers While his personal achievements are impressive, Brady also assists his teammates, constantly and risking injury to achieve other players' personal and team goals for other players. His actions instill trust in others and ultimately motivate them to play harder and contribute to the winning culture that Brady is known for. putting his reputation on the line Like Brady’s story, these traits are achievable in the business world. Please get to know your team, understand their desires and motivations, and construct a plan to achieve their goals. Lead by example, showing others what an elite level looks like, but also be on the ground, pushing your team higher and higher towards that level. Success isn’t achieved overnight, but over time, through effort and dedication, expect to see you and your team grow to their fullest potential. About the Author Lomit Patel is the Senior Vice President of Growth at Together Labs (formerly IMVU). Before Together labs, Lomit managed growth at early-stage startups, including Roku (IPO), TrustedID (acquired by Equifax), Texture (acquired. by Apple), and EarthLink. Lomit is a public speaker, author, advisor, and recognized as a Mobile Hero by Liftoff. Lomit's book Lean AI , part of Eric Ries' best-selling "The Lean Startup" series, is now available at Amazon .

How to Become the Greatest Leader of All Time: Tom Brady Style

Meet the Winners of Startups in North and Central America

Web3 has come to make our lives better. Some years ago, it all started with just flirting with crypto payments. Today, we already have a huge alternative market of digital assets, unlocking so many killer opportunities that have disrupted and beaten traditional approaches. And this is just the beginning. Great work is accomplished to make such disruption happen! However, despite all the achievements, the crypto market is still far from being a trading-friendly haven and has ample room for improvement. It’s currently highly fragmented, with liquidity and services split unevenly across various offerings around the globe. Such desynchronization makes trading risky and inconvenient, creates significant barriers for incoming retail traders, and turns off most of the institutional ones. To overcome this, there must be an innovative solution to put all the scattered pieces into one puzzle, which at the same time is in line with the key values of the disruptive economy: free and secure peer-2-peer (P2P) interactions without any middleman involved. was created to offer exactly this solution. Let’s take a look at how it will bring the crypto market to the next level. Yellow Network A Few Words On Crypto Liquidity Fragmentation At the moment, in the crypto industry, there are over 200 blockchains, featuring over 6,000 cryptocurrencies and tokens. Imagine all the crypto liquidity fragmented across a large number of centralized and decentralized exchanges (CEXs and DEXs), and how painful it is for both retail and institutional traders. To have access to a wide range of liquidity, a trader would need to open accounts with multiple trading platforms and entrust each one with their private keys. That means that the more crypto exchanges a trader operates on, the more they are prone to , as they take it on each trading venue. The same applies to and that are inherent in almost every existing digital asset platform. counterparty risk security liquidity risks Another problem is the different ways of trading execution on exchanges. CEXs and DEXs use a range of different APIs to exchange data based on systems like REST, Fix and WebSocket. This means that each time onboarding on a new crypto exchange, a trader shall invest significant time and effort to get connected with it. At the end, it’s simply hard and inconvenient to manage multiple exchange accounts at one time.
This is why, regardless of all shiny opportunities of crypto, many professional traders, especially institutional ones, still choose to stay within the traditional stock markets. The last one just seems more mature and capable to meet the main traders' needs: deep order books, low spreads and an ability to match large orders without slippage and destabilizing assets’ prices. Yellow Network is wired to give traders the same level of comfort with crypto, and as a result, bring it into the mainstream and mass adoption. Let’s break this down. The Solution to Liquidity Fragmentation Yellow Network offers to interconnect multiple scattered exchanges in one automated non-custodial trading hub, providing a user with the aggregated liquidity and price feed, as well as seamless high-speed cross-chain transactions at minimal fees. Let's take a look at the technology behind this vision. 3-Layers concept On of Yellow Network would be multiple blockchain protocols (ETH, BTC, Solana, etc.)  that validate transactions. As a well-known fact, blockchains have a lot of limitations in transaction throughput and their execution speed. The more transactions going on at once, the slower blockchain protocols work and the higher transaction cost will be. Apparently, blockchains alone are not efficient for trading needs. They do okay supplying the liquidity, but so far failed miserably to scale to a global high-frequency trading solution. Layer-1 To overcome their limitations, blockchain protocols are paired up with a scaling solution called “ ”. A state channel comprises a set of open-source protocols, smart contracts, interfaces, and software that allow users to transact with one another directly outside of the blockchain (i.e., off-chain) and minimize their on-chain operations only to the specific necessary sequences. Layer-2 state channels In particular, these on-chain activities are limited to the opening up and closing of a state channel between parties, and they validate only the final state between them after multiple transactions. As state channels do not require node validation for every transaction, they can handle the majority of user activities (trading, payments, etc.) with X-time more throughput and speed, than Layer-1 protocols. So such cutting the number of necessary on-chain iterations with the use of state channels allows to drastically reduce the costs and increase the speed of interactions. And the is Yellow Network, offering a , built on top of OpenDAX v4 technologies. The network’s Finex nodes and protocol allow to connect multiple exchange platforms in a broad trading environment, as well as to launch new DEXs and easily integrate them. The network will reach Layer-1 blockchains through Layer-2 state channels and procure low-cost high-speed cross-chain transactions suitable, even for high-frequency trading (HFT). It will also share the liquidity and price feed aggregated from all the exchanges integrated with the Network. Layer-3 P2P cross-chain overlay mesh network Non-custodial P2P trading Yellow Network facilitates non-custodial trading, which means that users will be able to deposit and withdraw funds using their addresses on a specific blockchain. So trading on Yellow Network, users do not face counterparty risk, as they remain in full  control over their private keys and digital assets. The Network is fully decentralized and preserves all p2p trading properties. For a user to become a “peer” on the Network and start transacting, they just need to open a state channel with the Finex node. As mentioned earlier, the opening and closing of a state channel happen on a blockchain where participants send a transaction with the initial state to open a state channel and a transaction with the final state to close the state channel. So all the transactions on the Yellow Network occur directly between the peers with the use of Layer- 1 and Layer- 2 combo with no intermediary involved. All peers participate in delivering messages throughout the Network, and can join and leave it at any time without disrupting it. Sharded Orderbook Yellow Network uses sharding as a method for distributing its aggregated order book across the Network nodes. The sharded orderbook has unlimited capacity for the Network’s participants' requests, and at the same time is resistant against any work interruptions, as it has no one point of failure. If any Network node goes down, it would in no way affect the global orderbook's accessibility by traders. How does Yellow Network help the end-user? Wrapping it up, here are the main benefits that an end-user will get through the Yellow Network infrastructure, whether they are a retail trader or an institutional one: secure Pp2Pp cross-chain in absence of the counterparty risk, deep assets liquidity, which means no risk of slippage and market manipulations by large-size traders, high-speed transactions, enabling even HFT trading, best assets prices, low cost of transactions, and user-friendly interface,  providing, at least, the same features as traditional stock markets. The “network effect” that Yellow strives to achieve for digital assets trading will eventually make the whole crypto industry more accessible and attractive for users. The higher the number of professional traders involved, the faster the disruptive economy will develop. Want to learn more about Yellow Network and cross-chain trading technology? Check out OpenDAX v4 stack GitHub: Follow Yellow Twitter: Join the public Yellow Network Telegram: Stay tuned as Yellow unveils the developer tools behind Yellow Network, brokerage nodes stack, and community liquidity mining software! https://github.com/openware/opendax https://twitter.com/Yellow https://t.me/yellow_org

An Intro to Web3 Multi-Chain Trading

At , our developers are busy. HackerNoon They are so busy, that our marketing department is having a hard time keeping up with all of the awesome new features they are creating and improving. They also seem to like deploying something and releasing it as ‘yours to discover.’ In other words, very low-key and covert. Which is adorable, but also much too discreet. The rest of the team at wants to change that up a bit. HackerNoon We want to honor them, and show gratitude that we appreciate their hard work. But also to make sure our users (and certain non-dev team members) are up to date with everything that is happening. About once a month or so, we will publish a list of new (or occasionally some we forgot) product features, and highlight some of the biggest ones at the top. Please be sure to follow this account to keep yourself posted, or check out the . About Section's: Software by HackerNoon Small disclaimer: You may already be aware of some of the ones below, please allow an adjustment period for this new process. Thank you! The Notable 4 The about page is the second most visited page on the average site (after the homepage). With this user about page, we are validating writers’ expertise and perspective, and giving readers a page they can be proud of on HackerNoon. So far, 6,635 About Pages have been created. . 1. Individual User About Pages : Some people are very psyched Thank you for your patience. 2. Editor 3.0 has YouTube Embeds! 3. The shop.hackernoon.com launch! We partnered with Stackcommerce to build an online shop to sell HackerNoon branded merchandise, and provide users with discounts on valuable tech tools and online courses. Users can now subscribe to different types of emails. Check out more information . 4. The Email Subscribe Options are as Nuanced as You Are: here Other Awesome Improvements/Creations With a few simple clicks, users can now select a topic/prompt of choice (such as , , or knowledge on a niche such as . They then will be directed to a draft page on and simply start answering the questions. Since its launch, this initiative has resulted in 483 quality stories from all corners of the web. Writing Prompts Templates : writers-exclusive interview opinion on the news data science) app.hackernoon.com NFTs in Blog Posts: Have you heard? You can embed NFTs in your blog posts! Read more about that here. The HackerNoon Pixel Font 2.0 is now open-sourced and available on and . HackerNoon Pixel Font 2.0: brand.hackernoon.com GitHub Read more about it here. of the backend: We migrated our database for the Noonies to Firebase, both for current and previous years to ensure our award links remain evergreen. The front end got a new lick of paint, a dark mode, and several speed improvements over past iterations. Last but not least, we resolved several SEO shortfalls from last year to boost organic traffic. A total revamp Noonies Voting Software Story URLs now no longer have random strings of letters at the end, which makes them more user-friendly and good for SEO. Cleaner URL Structure: was built into the editor system. The Plagiarism Checker get the love they deserve! Users who left a draft open for longer than x days now get an email from Natasha reminding them to take care of their mental health AND finish the draft. Abandoned Drafts Elements such as the welcome message, and the ability to drag and drop convos around have been improved and/or implemented. and counting! Slogging Back-End Improvements: 277 stories are currently published A more colorful HackerNoon FTW! Users can choose from 4 default color palettes. Users who do this stay x time longer on site. Read more about that Choose Your Color : here. : Certain trusted, highly qualified users are now able to bypass the editorial process and publish their own stories. We are working up to our desired rate of publishing by empowering the top contributors to earn and leverage the publish button. We are flattered that some users still choose to submit to the editors anyway because 'we have better headline practices' <3. Examples and . Verified Writers (invite-only, for now) here here We're proud to announce a revamped Editor Dashboard and in-app workflow to match our evolving and expanding editorial team.  It has WoW stats on stories published, scheduled, rejected, and more! Editorial Dashboard 2.0! Read more about the overall growth of HackerNoon in The State of the Noonion: The Year of Profitability and Product Renaissance This post was written and compiled by Linh Dao Smooke and Ellen Stevens.

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How blockchains will reshape the Covid-19 vaccine supply chains and how a startup backed by Bill Gates´GAVI is at the forefront of the multi-billion $ bonanza Supply chains are probably the weakest link in complex business architectures. The "just in time" inventory needs of modern consumption, the rampant consumerism, the extreme globalization and connectivity, made supply chains all too complex, fragile, and more than ever exposed to sudden shocks. Then came Covid-19 which put supply chains under considerable strain and made their weaknesses and lack of resilience all too apparent. But technology in the form of DLTs/Blockchains and IoT devices can save the day. They can dramatically improve supply chain management, make them more efficient and more resilient. Because blockchains/DLTs offer - through decentralization - a secure, transparent, incorruptible, immutable, auditable and efficient way to record digital data, they are the perfect tool for managing supply chains. Coupled with IoT - which sensors can record all sorts of external data such as speed, temperature, humidity, time, exact geo-localization, opening and closing of packaging and the breaking of seals, etc. - the data can be processed and analyzed in real-time to enable an immediate managerial response. The Challenges When looking specifically at the pharma industry, the picture is not rosy. , while companies like Walmart, Apple or Zara have "superb supply chains", pharma industry´s  supply chains are "neither flexible nor cost-effective". According to PWC More specifically, the major challenges that the Covid-19 vaccine distribution will unleash on the pharma industry, can be summarized as follows: (i) the need to use a different supply chain as with other products. Likely much wider and extended, therefore more complex and difficult to manage. Basically the need is to track down everything and everyone from medical components (i.e. suppliers of ingredients) to the final patient receiving the vaccine; (ii) the need to scale up and down deliveries based on epidemic data and demand; (iii) the need to compress delivery time and comply with cold chain constraints; (iv) the need to monitor stock inventories in real time, avoid shortages and manage timely delivery; (v) the need to collect and handle vital epidemiological data (this will be the "KYP", Know Your Patient process) and share it with a multitude of stakeholders such as the authorities, hospitals, family doctors, pharmacies, etc. This is also vital in case vaccines are defective or have side effects which require an immediate suspension of the treatment or a product recall; (vi) the need to incorporate IoT devices to prevent counterfeit and manage cold-chain constraints; (vii) the need to manage increased complexities, such as different producers and diverse types of vaccines which are not compatible with each other. Since vaccine shots will be administered at intervals, one must make sure that people get the second or third shot of the very same vaccine and not of a different one. Mistakes here can cost lives and potential liabilities could be huge. Some of the above issues are clearly not unique to the Covid-19 vaccine, but are made more pressing by its criticalities such as, for instance, counterfeit risks and the cold-chain integrity. While degrees, some types of Covid-19 vaccines will need to be stored at much lower temperatures, between -60° and -90° degrees. That is a totally new challenge for the cold-chain. normally a pharmaceutical cold-chain operates with temperatures reaching -25° Also counterfeit drugs are one of the biggest problems that the industry faces today. The worldwide counterfeit drug market is valued at over US$ 200 billion. Counterfeit drugs are said to be responsible for the death of more than 500,000 people every year. According to WHO estimates, — including pills, vaccines, and diagnostic kits — are fake or substandard. Here you can find a . 10% of all medical products sold WHO study on that topic For the European Pharmaceutical Review, counterfeit or substandard drugs sold in developing countries are at least 30%. For this reason some countries have introduced strict regulations for tracking drugs in the supply chain. In the USA for instance, the was passed which mandates for a unique ID on the drug. Therefore the integration of IoT devices and the blockchain/DLT technologies is now essential. Drug Supply Chain Security Act An Italian company named has developed a unique "printing fingerprinting" technique, , which can be incorporated into a QR code to make it unique and non-counterfeitable. The ViseQR was conceived to protect "Made in Italy" products from counterfeiting, therefore this patented technology is built to be flexible enough to be applied to any type of product and industrial sector. Viditrust called ViseQR Technologies such as the ViseQR, coupled with IoT devices and then incorporated into blockchains/DLTs, are the solutions that Big Pharma badly needs today. How this can be done by Techskill-Brew. is visually well explained in very simple terms in this article The Players A few companies have been merging blockchains/DLTs with IoT and sensor devices in order to build the infrastructure necessary to handle the complex Covid-19 vaccine supply chain constraints. Some have gone a step further and enabled the deployment of the so called , i.e. pieces of code which automatically execute pre-set instructions when pre-set conditions are triggered. smart contracts solutions for the pharma industry are based on SAP`s  corporate permissioned DLT and deploy smart contracts which are triggered whenever the IoT sensor/device registers a pre-set condition such as, for instance, a temperature falling below or raising above a certain threshold or the breaking of the seal which ensures the integrity of the packaging and so on. Modum.io In this case, the smart contract will trigger a pre-set instruction, such as the immediate product recall, or it may signal the recipient that the drug should not be used and be returned to sender because defective.  Another player is , which proposes similar use cases and products but uses the public Ethereum blockchain. Ambrosus The difference is that Ambrosus - being run on the Ethereum blockchain - offers a more dynamic environment for developers and community members to build dApps, extensions and protocol upgrades.  This enables the exploitation of synergies and interoperability with other Ethereum-based protocols and allows the integration and functionality of Ambrosus dApps. The San Francisco based has already onboarded key industry players such as Pfizer, Gilead and Bayer. They have raised tens of millions of US$ and have launched , a consortium which develops the blockchain based supply chain infrastructure for its members running on the , which was built by . Here each member owns and operates a node and the blockchain uses a . Chronicled.com Mediledger Ethereum Parity client Berlin based Parity.io PoA (proof of authority) consensus algorithm Enter WEF, WHO and GAVI´s darling startup company But a more obscure Indian startup , based in Hyderabad and Singapore - which now boasts also a US address in Cupertino - might actually become the unforeseen prime candidate to win the Covid-19 vaccine supply chain management race and benefit from the multi billion bonanza paid by governments worldwide with taxpayer´s money. named Statwig does not tell what type of solutions they are developing nor what type of technologies and blockchain/DLTs they use. Nonetheless, with powerful and well-connected sponsors, backers and partners such as the - the brainchild of the ubiquitous duo - they are certainly well placed to win a big fat contract. Statwig´s website WEF, the WHO and the GAVI Alliance Bill and Melinda Gates The company - defined as a startup in this - was awarded a US$ 100.000 grant from the UNICEF Innovation Fund. In July 2019 the company was shortlisted for GAVI´s Infuse program, " ,” said the CEO Siddharth Chakravarthy. When and how the GAVI, the WEF and the WHO got involved with Statwig is not known. But things for the company seem to have taken a sudden turn for the better this year in 2020. December 2018 article There is a scope to enter into a long-term arrangement with GAVI. The Bill & Melinda Gates Foundation is backing the GAVI programme In May 2020, at the end of the first Covid-19 wave, Statwig´s Facebook page boasted that the company had joined the Chinese family. How much the Chinese accelerator has invested in Statwig is not known, but their web site says, "Statwig is a startup for efficient tracking of vaccine and food supply chain using blockchain and IoT. Its partners include UNICEF and GAVI - (they forgot to mention the all too important WEF, to which " Statwig fits perfectly like "the cherry on top of a cake") - ." Longhash venture accelerator Great-Reset" agenda and are in consideration to handle the tracking and monitoring of the Covid-19 vaccine which is slated for a 2021 release BINGO!! Then, in July 2020, the apotheosis. hints at the startup as the candidate to none other than the hugely complex task of managing the Covid-19 vaccine global supply chains. No indication whatsoever on how they plan to do it, how their "vaccine supply chain management platform" works, what type of technologies or what blockchain/DLT will be used. Thanks god they concede at least that they will be using, "QRcodes [Barcodes/Serial Numbers] printed at unit-levels to track the vaccines from the manufacturer to end-consumer...". A celebratory WEF sponsored article Yeah, that´s revolutionary. That invention dates back to 1994 and we have seen it on every single product and every single market shelf for the last 20 years. But hey who cares, if you are "lucky" enough to be awarded big fat contracts then you can always sub-contract someone else to do the job.  Or why not, you might as well buy from the Italians the above mentioned patent to the unique . At least this is an evolutionary step ahead of Statwig´s good old QRCode. ViseQR For all these reasons one could confidently bet on Statwig.  Bill and Melinda have the "animal spirits" and showed consistent ability to pick winners. Their foundation has been making large grants to the likes of , and as well. The foundation is certainly not new to which then benefit also from grants from affiliate entities like GAVI or the WHO, in a sort of communicating vessels system. Pfizer Moderna CureVac betting large stakes in listed companies . Their unmatched web of interests range from investments in pharma companies to massive grants to authorities such as the WHO and the GAVI Alliance, to large contributions to the WEF and now the sponsoring and financial backing of Statwig via the GAVI Alliance, the WHO and WEF. They have been doing this for almost 20 years Does anyone see a potential conflict of interest? Conclusion No doubt that both Statwig´s CEO and "philanthropists" Bill and Melinda will be very satisfied with the outcome. Sooner or later however uneasy questions will be asked and someone will raise more than eyebrows. . Then they will have to come clean with their web of seemingly conflicting economical and humanitarian interests Is this sheer profiteering in a philanthropic guise? Moreover, when philanthropy becomes a tool to serve vested interest? (c) www.bianconiandrea.com - 2020 ************************************************************* 85d1c86b8cef11eb3546a89f2fe7672532e4f95eaccc0a01da5f792a1625bdb7 #crypto #blockchain  @thinkblocktank @untitled-inc #supplychain #covid-19 #billgates ************************************************************* If you enjoyed this post, please “clap” Xtimes in the bottom left corner so it will be shared with more people. Many Thanks ************************************************************** : The website and the information contained herein is for general guidance only and it does not constitute legal advice. As such, it should not be used as a substitute for consultation with lawyers on specific issues. All information in this paper is provided "as is", with no guarantee of completeness, accuracy, timeliness or warranty of any kind, express or implied. Legal Disclaimer : The website and the information contained herein is not intended to be a source of advice or credit analysis with respect to the material presented, and the information and/or documents contained in this website do not constitute investment advice. Investment Disclaimer (c) www.bianconiandrea.com - 2020 Also published at https://andreabianconi.medium.com/and-the-covid-vaccine-winner-is-the-blockchain-ceb4fdbacca5

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