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Meet the Winners of Startups in North and Central America

DeFi continues to garner the attention of retail and institutional investors with incentivized participation, one of the keys to Bitcoin’s continued success. Unlike most of us in 2020, Decentralized Finance (DeFi) has been having a very good year, becoming one of the most compelling innovations in the blockchain space with over $12.27 billion of value in the sector (based on 44 providers tracked by DeFiPulse). locked There are several factors at play in DeFi’s success, but like a hit song suspiciously reminiscent of the Beatles, the wild enthusiasm seems to be based on a familiar theme of incentivization — just like Bitcoin, but this time not . farming, mining has captured crypto investors’ attention by allowing investors to earn returns by providing stabilizing liquidity to DeFi protocols. Yield farming In function, yield farming resembles the innovative (and famously successful) formula devised for Bitcoin mining which provides long-term incentivization and returns for active members positively supporting the ecosystem. In the case of DeFi yield farming, users are similarly rewarded for positive participation, earning yields for buying and holding platform-native tokens. The demand for DeFi tokens has grown with more exchanges all over the world adding them to their basket of tradable assets, despite the threat to centralized finance that DeFi poses. NDAX.io is the latest exchange to add DeFi, with an announcement touting support for Chainlink (LINK) for the audience. Bilal Hammoud, NDAX.io President, CEO, and Founder, said “2020 has shaped up to be the year of institutional adoption of Bitcoin, Stablecoins, and decentralized finance…which provides retail and institutional investors exposure to new crypto products...” (Disclosure: I have in the past contracted with NDAX.) Canada crypto investing Changpeng “CZ” Zhao, CEO of Binance, and potential to cannibalize his own business as his company launched their own DeFi initiative, Binance Smart Chain while maintaining their position as the world’s largest exchange by trade volume. Zhao said, “I’m always much more worried about if we have users using the product. There are always multiple options for business models, so the key is to build something that’s useful.” acknowledged the contradiction DeFi is still considered an untested, high-risk concept by some crypto investors and dubbed the DeFi Pulse Economic Safety Grade which measures the risk of protocols becoming insolvent. DeFi Pulse recently announced a risk grading system It took DeFi three years to build momentum, but at over $10 billion in investments, many new protocols are looking to capture the imagination of crypto investors. Of course, the vast majority of efforts will fail or consolidate over time but the promise of yields based on participation continues to drive enthusiastic participation from users. Justin Roberti has a background in media and fine arts and has been writing and doing PR/marketing for over 20 years for Fortune 500 and startups in media, gaming, consumer tech, mobile tech, fintech, and blockchain. He writes about tech, media, and web culture. He is the PR Director for blockchain agency Zage.io .

DeFi’s Success Modelled on Bitcoin’s Formula 

A plain-talk explanation of crypto for people who just want to get it over with. Ever since I started representing blockchain startups 3 years ago, I have had many opportunities to explain what crypto is and why it’s not completely a scam — mainly to friends, family, and neighbors. I cannot overstate the degree to which “normies” think all crypto is a scam. It’s a legitimate extension of traditional finance filling a role that has only , and during the economic crisis that is certain to follow. grown during the COVID-19 crisis For those of you who are wishing you’d stop hearing so much about Bitcoin and kind of wish it would go away — . I don’t know where it’s future fortunes lie but I think it’s safe to say it will have some value for the next ten years, whether you think that will be $100,000 or $199, so it’s better to understand than not understand. Bitcoin has had a good 2020 There are a few common misconceptions you have to dispel to understand the what and why of Bitcoin… “Bitcoin is a scam” Bitcoin is a brilliant innovation — it gave us a platform for a truly independent and decentralized form of currency. It is still the most successful and brilliant practical use case of blockchain technology to date, 11 years after its launch. Bitcoin made some brilliant moves incentivizing honest participation (including miners) long-term, and basically getting people to invest in the concept that this untethered asset has value. Bitcoin has been used by scammers, it has been the center of various scams, but Bitcoin is not responsible for criminals that use it any more than the US Dollar is responsible for criminals that use it as a tool for crime. Of course, Bitcoin not being a scam says nothing about the veracity of the more than 2,000 altcoins that can be purchased on exchanges all over the world. Bitcoin showed us that communities could be built on positive participation and collective belief and that those communities can assign value to a currency, which means that currency is independent of state. As a U.S. citizen, I can see the appeal of independent of state very much in 2020. 2. “Bitcoin isn’t worth anything” If you think that Bitcoin has a value based on nothing, that just isn’t true. It’s just harder to define. The fact that Bitcoin is staked to no tangible assets has actually been a strength — it works as a deflationary asset. When nothing has value, Bitcoin still has value. What Bitcoin is really staked with is the effort and investment that created the collective belief that Bitcoin has value. National currencies like the U.S. dollar are a sort of investment, deriving value because the holder believes in the strength of the U.S. economy. But like any successful product, Bitcoin filled a need that pre-dated its launch. There is a real desire among the wealthy and the highly-independent investor who wants assets independent of state and all the uncertainty that global politics bring. Of course, Bitcoin is the shadow of the traditional financial system — it’s not truly independent, as it is subject (inversely) to traditional market movements (particularly the S&P 500, whom some are suggesting dictates BTC movements — when the S&P is down, Bitcoin goes up.) Bitcoin hasn’t been around long enough to be a reliable store of wealth and anyone with a financial background knows that — but institutional investors are moving the market more than ever. The suit-wearing investors of traditional markets are getting on board with crypto (and their own blockchain in the case of JPMorgan’s IIN network which has over 300 banks enabling ) but not because they it is a reliable store of wealth — it’s because they still think it’s safer because USD, oil & gas, and even gold have been outperformed by Bitcoin. Bitcoin transactions know 3. “You Can’t Buy Anything with Bitcoin” This just isn’t true anymore. of places you can spend crypto, including: Bitpay keeps a curated directory Buy Gift cards from Amazon, Delta, DoorDash, PapaJohn’s, Red Lobster, Uber, Wayfair, and many others. Entertainment & Gaming from Microsoft, Twitch, and DishTV, and others. Donations to The United Way, American Cancer Society, and the American Red Cross, among others.Electronics from NewEgg and hundreds of other vendors for jewelry, food, web services, and more. 4. “Bitcoin just isn’t for me.” Judging by the principles of Bitcoin, as expressed on their , Bitcoin is for everyone. That’s the whole idea. white paper If you fit any of these categories, it’s for you: If you live in a country with an unstable fiat currency.If you don’t have access to reliable traditional banking — 2 billion people all over the world are unbanked or underbanked. If you don’t have access to reliable online payments. Bitcoin won’t necessarily be usable for all of your expenses, but if you have access to a smartphone you can set up decentralized banking, store your wealth, and make payments using crypto even if local currencies and banking are unreliable.If you deeply distrust the nation you live in and the stability of its currency. Bitcoin is the hedge position du jour for investors who see trouble on the horizon from the U.S.’ and the world’s “No-Good, Very Bad Year”. People don’t consider a global economic collapse to be inevitable, but they want to hedge against the possibility. It’s smart not to keep all your assets in one basket, after all, and not put all your faith in one system. Don’t Worry, the Suits have come to Save Us represent a larger portion of bitcoin transactions than ever before and that trend is only increasing. That means good things for the mainstreaming of cryptocurrency, but it also means less Bitcoin is going to be held by the bleary-eyed blockchain developer or entrepreneur and more of that wealth will be held by people in sharp business attire — some independently wealthy, most working for traditional financial institutions. Large-volume and institutional investors Many exchanges like Kraken and Coinbase have OTC desks to handle high-volume transactions and service these large and institutional investors (usually starting at $50,000 purchases). OTC desks give big buyers the ability to access liquidity pools without actually having to find the “BTC whales” who are sitting on hoards of Bitcoin gold, some of whom might want to sell. NDAX.io, a Canada-based trading platform (which I’ve consulted with through past contracts), has recently revamped and rebranded its OTC desk to include improved service — including an AE to service your account and 24x7 hotline to ask questions about your transactions. In other words, the level of service people coming from the traditional banking world might expect. Don’t Panic (Crypto is Coming for you Anyway) Douglass Adam’s advice from “The Hitchiker's Guide to the Galaxy”, published in 1979, is still great advice. "Don't Panic". Don’t worry, crypto is likely to be part of your life whether you choose it or not. Certainly, blockchain will power the back end of sites you use all the time, like t. But if Facebook’s Libra project doesn’t have billions of consumers taking out credit loans and spending in crypto to earn savings in the short term — then another monolithic tech company will come along and fill the void. Amazon which already has its own projec People want more options. Projects like Libra is ready to give us another option. I’m not going to opine whether it should be allowed to succeed — but let’s not kid ourselves that stopping Libra will stop the tide. Crypto will become mainstream, particularly if people can use it without ever being aware of crypto’s involvement. You will know crypto has really become mainstream when they stop talking about it as a separate animal from other electronic payments, and blockchain will be accepted when it has become as exciting in headlines as any other coding platform. The hype will die and the true useful life of blockchain and crypto will begin. Justin Roberti has a background in media and fine arts and has been writing and doing PR/marketing for over 20 years for Fortune 500 and startups in media, gaming, consumer tech, mobile tech, fintech, and blockchain. He writes about tech, media, and web culture. He is the PR Director for blockchain agency Zage.io and sometimes-consultant for NDAX.io . (Photo by Marina Vitale on Unsplash )

Stop Procrastinating: Time to Learn About Bitcoin

Canada’s relationship with blockchain and cryptocurrency has had dramatic highs and lows. Though some world-leading blockchain technology like Ethereum started as Canada-based projects,  Canada has not embraced crypto with the same zeal as some other countries. And unfortunately, bad actors in the crypto community have given Canadian regulators and the public reasons to worry. The Canadian crypto ecosystem has been slapped three times in the past two years. In January 2019, QuadrigaCX made global news when Gerald Cotten, the 30-year-old co-founder and CEO of Vancouver-based crypto exchange, QuadrigaCX, died while on honeymoon in India. He was, it seems, the only person with access to $190 million of funds in crypto and fiat money, which was the majority of funds stored on the exchange. In November 2019, Einstein Exchange, Vancouver, British Columbia-based crypto exchange, suddenly closed its operation, literally locking its physical location while founder Michael Ongun Gokturk went missing. British Columbia Securities Commission (BCSC) took control of the Einstein Exchange and investors were owed C$16 million. In July 2020, Toronto-based Coinsquare was found to have been engaged in “wash trading”, with 90% of transactions faked between Q4 2018 and Q1 2019. Coinsquare CEO Cole Diamond, founder Virgile Rostand, and executive Felix Mazerwere found to have knowingly “authorized, permitted or acquiesced” to the fraudulent practice. Over C$2 million in fines were paid and all three men resigned. However, despite the highly publicized scandals, the Canadian government seems to value the potential of blockchain and crypto at a macro level. recently showed that COVID-19 has advanced the adoption of blockchain just as it has increased digital adoption, globally. The survey showed that 76% of Canadians see cryptocurrency as an alternative to fiat currency. Deloitte’s 2020 Global Blockchain Survey So what is the best way to buy Bitcoin in Canada? Canadian Crypto Exchanges Here is an overview of some of the leading exchanges serving Canadian audiences. 1. Coinsquare Since 2015, the Toronto-based Coinsquare has been dedicated to providing a safe, affordable, and simple way for users to exchange cryptocurrencies online. The company has grown in the past few years -- but the scandal of this year and has hurt its reputation and sent many users looking for another solution. resignation of leadership Pros With 5 fiat currencies and 10 cryptocurrencies available to trade, there are many options for the users. Coinsquare employs all standard security measures to ensure safety and privacy. Through storing 95% of all funds in offline cold wallets, extensively testing its technology against distributed denial of service attack (DDoS), and having close relationships with a number of Schedule 1 Canadian Banks. Though its site’s simple UX seems to be catered towards entry-level traders, they have also done a lot of work to attract and support high-networth investors by opening up a mining venture arm and a capital markets division. They offer a program for Coinsquare Wealth, targeted to more advanced traders. It is an exclusive service for those who trade over 25k worth of orders at a time. Users receive exclusive benefits including discount funding/withdrawal fees, faster withdrawal speed, and a dedicated wealth director. Cons There are only two ways of depositing money, through e-transfer or wire transfer. With deposit processing times of 1-3 days and withdrawal processing times of 1-9 days, the overall process can be frustrating, especially since they place withdrawal holds. Its fees are among the highest of all exchanges. Ethical issues concerning the exchange’s business practices have given many users misgivings concerning doing business with Coinsquare. It will be up to new leadership to rebuild that trust however they can.- based 2FA user account security system was proven to be insecure in the past. 2. NDAX.io Founded in 2017 in Calgary, NDAX.io’s goal is to make it easier and faster for people to buy bitcoin in Canada. (Disclosure: I work with NDAX.io as one of my clients when I’m not writing articles.) They keep a physical office, a support line for resolving issues by phone, relationships with traditional banks, and have worked proactively to stay ahead of the regulatory curve, so they offer a mix of traditional economy accessibility and support and leading-edge security and compliance. Pros NDAX offers a clean, easy trading platform that doesn’t overwhelm newbie crypto investors and makes transactions fast. NDAX.io offers leading security on their platform with 95-98% of digital assets offline in cold storage. It uses multiple data servers which are monitored 24/7 and employ Multi-Signature technology to keep assets secure. To fund your account, you can use Interac e-transfer, Wire Transfer, or Bank Draft / Certified Cheque. For  support, they offer live chat on the site, email, and phone support. NDAX is registered as a Money Service Business (MSB) with FINTRAC. They work closely with regulators to meet the requirements of today and regulations that are not yet in effect, essentially future-proofing its business from a regulatory POV. NDAX allows you to buy and sell 8 coins including Bitcoin, Ethereum, Litecoin, XRP,, EOS, Dogecoin, Cardano and Stellar. They have announced that they will be offering 4 new coins/pairings in Q3 2020. NDAX offers low fees that are especially advantageous for more experienced traders - no fee on deposits, flat fee withdrawals and 0.20% trading fees. NDAX registration process is quick (approved within 15 minutes) and relatively simple. If you do have any problems, its support is very responsive. It also offer training guides, advanced trade training, and product tours to help you get up to speed. Cons NDAX is devoted to serving a wide range of Canadian users -- meaning its finest points are not terribly sexy from an outside POV. Security, compliance, transparency, and user-centric customer service are important to have but don’t make exciting sound bytes. Users accessing more advanced trading features may find themselves quickly out of their comfort zone. NDAX doesn’t have the international capabilities of larger exchanges like Kraken, which means you may have to use other exchanges as well to deal with multiple fiat currencies, etc. American Crypto Exchanges that Serve Canadian Residents Below are crypto exchanges based out of the United States that serve Canadians. 3. Coinbase Founded in San Francisco in 2012, the Coinbase mission is to allow anyone to easily and securely access Bitcoin. It offers a simple interface preferred by new crypto buyers. Pros Coinbase is one of the largest exchanges, supporting over 100 countries and over 30 million customers around the world. Coinbase has a wide array of services but its main service allows users to buy and sell Bitcoins through a credit card and debit card. Coinbase UX is optimized to the inexperienced buyer. Coinbase offers on-platform cryptocurrency conversions allowing users to make complex transactions without leaving the platform. There is a 2.0% fee for conversions. Coinbase does have an extensive knowledge base -- but does not have a good reputation for customer support. Cons Fees are relatively high and support can be problematic. Coinbase uses a flat fee between $1.50 and $3.00 for transactions below $200 or a percentage of the transaction (whichever is greater). Most transaction fees are 1.49% for standard buy and 3.99% for credit card buys -- meaning that credit purchases are potentially quite higher.The market price on Coinbase Pro +0.5%, which is better than with standard accounts but fees are not competitive for larger or institutional buyers. Coinbase is rated badly by the Better Business Bureau for . failure to respond to hundreds of customer complaints Though Coinbase is popular in Canada, it is not Canada-based which can cause delays in transactions. 4. Kraken Founded in 2011 in San Francisco, Kraken claims to be the largest Bitcoin exchange in terms of euro volume and liquidity. Its strong reputation is supported by low transaction fees, a wide range of features, and overall security. Pros Kraken follows industry security practices such as keeping , two-factor authentication, and 24/7 surveillance on the exchange so that nothing comes in or out without being monitored. 95% of user funds in cold storage They were one of the first exchanges to prove that it was keeping its customers’ money safe using an independent cryptographically-verified audit (proof-of-reserves audit process). Kraken offers three different types of accounts (starter, intermediate, and pro) with different limits and features in order to cater to any experience level. Its futures and fiat trading are standout features that aren't often found on other exchanges. The ability to trade with five different fiat currencies allows users to make trades without having to visit other exchanges. The sign-up process differs based on which account you choose to open. If signing up as a starter account, only basic info is needed. For an intermediate account, the requirements are similar to other exchanges, with photo ID and proof of address. For an advanced account, AML verification and financial statements are needed additionally. The verification period on Kraken was very fast (I was verified in about 15 minutes). Cons Kraken is a powerful platform - and also potentially complicated and slow. Though it has many tools available, those who are just starting out may be overwhelmed and confused. The process of actually buying cryptos on the site can take a long time. Through creating an account, waiting for verification, depositing fiat currency via bank transfer and waiting 1-5 business days for the deposit to reach the Kraken account in order to finally be able to exchange fiat currency for crypto, takes a long time in comparison to other exchanges. Though they say its fees are the lowest in the industry, with a volume-based fee model this is only advantageous to pro-traders. Finally, since Kraken isn’t based in Canada, wiring money through an intermediary bank means extra time and fees. Summary Based on BTC’s current performance, it’s safe to say that deflationary assets like crypto are gaining traction and have not reached their high-water mark of value. It’s not too late to get on board the “crypto train”. Scandals and widespread adoption aside, the train has barely begun to leave the station. Based on their individual capabilities, it is likely that a newcomer to crypto investing may want to try several exchanges -- starting with a simpler platform and exploring others as the user looks for more coins and more advanced options. If there is a lesson to be learned from the global pandemic and economic fallout, it’s that governments are not infallible. So, the average consumer may be better served by diversifying than by keeping all of their liquid wealth in their national currency. Remember -- if you fail to invest in crypto or traditionally traded assets you are NOT opting out of the investing game, you are just keeping all your wealth in one fiat “basket” which history has shown can sometimes go badly, especially during global economic upheavals. (Disclosure: I work with NDAX.io as one of my clients when I’m not writing articles.)

Where Can Canadians Buy Bitcoin: A Review of The 4 Most Popular Crypto-Exchanges

Use Beta Distribution and Thompson Sampling to Beat The Multi-armed Bandit at the Casino

Startup founders keep asking my colleagues from Flyer One Ventures and me to sign non-disclosure agreements (NDAs) before they start sharing any metrics. It's easy to spot founders who are likely to want an NDA: These ninjas send investors decks without numbers, implying that everything they work on is classified information. In reality, however, your idea is no secret, and no one will steal it — especially not VCs. You don't look cautious when asking to sign an NDA; you look weird. From a legal point of view, NDAs significantly increase the time for due diligence and costs for lawyers, as all NDAs are different and often nonstandard. Add to it a non-compete clause, and nearly every investor I know will likely turn away. So take a deep breath and stop worrying. Here are five reasons why nobody would copy your idea. Stealing ideas isn't an option for VCs When investors hear a good idea, they don't think about leaving their VC firms to launch a similar startup. They spend years building their reputation, trust, Twitter following and media presence to raise a fund and start investing. Quitting the job is not an option. In most cases, venture firms don't have any spare employees to copy a random product: everyone is busy solving current problems – helping portfolio companies with fundraising, doing due diligence for new startups, and spending hours on social media. Also, investors can't patent your idea when they hear it: It takes up to 3 years to obtain a patent in the U.S. and up to 5 years to register it in Europe. VCs won't just spend three years getting a patent for an early-stage startup's idea, which they just heard about. Theoretically, investors can leak your idea to your competitor. But signing an NDA with a VC doesn't prevent your rivals from understanding what and how you do. If they want to copy you, other founders can pretend to be potential clients or hire someone to do it for them. You are already ahead of potential copycats Even if a VC leaks your idea to friends or colleagues, it will take 6 to 12 months to bring it to life. It will take even more time to get the first clients. Your startup will already be way ahead in raising Series A. It takes months for startups to research, build a minimum viable product, fix bugs, do customer development, find the first clients, and actually make money. Plus, budget some time for founders to cry when one of these stages doesn't go according to the plan. Even if other founders have endless financial resources, they still need time to hire motivated people, mentor them and have them build a decent product that fits the market's needs. Potential copycats will need a lot of time, financial resources, and motivation to do the same. The probability that the copied idea will be better than the original and that everything will go smoothly is lower than your chances of becoming a unicorn. Besides, there's no guarantee that your idea will always work, even a good one. Building a startup is a process of iterations. You don't just come up with one single idea and use it forever — you adapt. Large companies don't care about raw ideas In 2020, Alphabet earned $258 billion; Meta made $118 billion and Netflix — $30 billion. Even if you're building a business intending to make $100 million in seven years, that kind of revenue will add less than 1% to a big corporation's financials. The big tech companies would better buy your startup in seven years instead of spending time and cash to build something similar. Why then, do large businesses often ask employees to sign NDAs? In their world, the rules are different. Amazon, for example, may have the resources to take a huge market share before anyone knows about it, while startups usually don't have the same pace and scale. their The monetary value of the losses for Tech giants is huge if their idea is stolen by other corporations. It's not just a verbal idea — it is hundreds of millions of dollars of market share. Startups often don't have the same scale, especially in the early stages. Your idea is a hypothesis only you can turn into a business All ideas are untested hypotheses, which need years of validation, and thousands of iterations, and might not work eventually. Even if you have tested the idea and think it's the one to work in your market, there's no guarantee that this recipe will work elsewhere — for every client and every startup. Plus, potential copycats can copy only the most obvious things. Yes, they can make an identical product. Yes, they can hire people with the same qualifications. Yes, they can set the same price. But they can't copy your thinking, communication with clients, management skills, and network. If someone dresses like you, tries to talk like you and dyes his hair like yours, they don't automatically become you. Your core asset — motivation Suppose someone left their job to launch a business, hired a small team with their savings, and spent months convincing their families not to leave them for good. In that case, they already have more motivation to turn an idea into success than a person/company which only wants to make money by copying one's product. People driven solely by the wish to make money give up when they face problems. Why bother if, nowadays, they could make a picture of a funny ape and sell it as an NFT for half a million dollars? (not anymore, but still) By contrast, people with deep personal motivation could only be stopped if they tried everything and nothing worked. In most cases, they never stop because they can pivot, raise more money, convince first employees to work for free for a while, and finish what they've started. If you want to cement your startup idea for yourself by forcing people to sign NDAs until you find inspiration to execute it, no NDAs will help you. Running a startup is about hard work, stress, problems, and only then success. And sharing ideas with investors, potential buyers from large corporations, or other founders will bring you closer to succeeding. Sharing is a good way to collect feedback and brainstorm together. Having someone unbiased to listen to the hypothesis may provide even better solutions to the problem. Not sharing, in turn, is a good way to get stuck and have no fresh hypotheses to move on with. It may be hard for you to trust strangers with your ideas, but don’t forget that VCs are supposed to trust you with other people’s money and reputation. Originally published . here

Startups Don't Need NDAs: 5 reasons Why Nobody Will Steal Your Idea

After my latest post about how to build your own RAG and run it locally, today, we're taking it a step further by not only implementing the conversational abilities of large language models but also adding listening and speaking capabilities. The idea is straightforward: we are going to create a voice assistant reminiscent of Jarvis or Friday from the iconic Iron Man movies, which can operate offline on your computer. Since this is an introductory tutorial, I will implement it in Python and keep it simple enough for beginners. Lastly, I will provide some guidance on how to scale the application. Techstack First, you should set up a virtual Python environment. You have several options for this, including pyenv, virtualenv, poetry, and others that serve a similar purpose. Personally, I'll use Poetry for this tutorial due to my personal preferences. Here are several crucial libraries you'll need to install: : For a visually appealing console output. rich : A robust tool for speech-to-text conversion. openai-whisper : A cutting-edge library for text-to-speech synthesis, ensuring high-quality audio output. suno-bark : A straightforward library for interfacing with Large Language Models (LLMs). langchain , , and : Essential for audio recording and playback. sounddevice pyaudio speechrecognition For a detailed list of dependencies, refer to the link . here The most critical component here is the Large Language Model (LLM) backend, for which we will use Ollama. is widely recognized as a popular tool for running and serving LLMs offline. If Ollama is new to you, I recommend checking out my previous article on offline RAG: Basically, you just need to download the Ollama application, pull your preferred model, and run it. Ollama "Build Your Own RAG and Run It Locally: Langchain + Ollama + Streamlit." Architecture Okay, if everything has been set up, let's proceed to the next step. Below is the overall architecture of our application, which fundamentally comprises 3 main components: : Utilizing , we convert spoken language into text. Whisper's training on diverse datasets ensures its proficiency across various languages and dialects. Speech Recognition OpenAI's Whisper : For the conversational capabilities, we'll employ the Langchain interface for the model, which is served using Ollama. This setup promises a seamless and engaging conversational flow. Conversational Chain Llama-2 : The transformation of text to speech is achieved through , a state-of-the-art model from Suno AI, renowned for its lifelike speech production. Speech Synthesizer Bark The workflow is straightforward: record speech, transcribe to text, generate a response using an LLM, and vocalize the response using Bark. Sequence diagram for voice assistant with Whisper, Ollama, and Bark. Implementation The implementation begins with crafting a based on Bark, incorporating methods for synthesizing speech from text and handling longer text inputs seamlessly as follows: TextToSpeechService import nltk
import torch
import warnings
import numpy as np
from transformers import AutoProcessor, BarkModel

warnings.filterwarnings(
    "ignore",
    message="torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.",
)


class TextToSpeechService:
    def __init__(self, device: str = "cuda" if torch.cuda.is_available() else "cpu"):
        """
        Initializes the TextToSpeechService class.
        Args:
            device (str, optional): The device to be used for the model, either "cuda" if a GPU is available or "cpu".
            Defaults to "cuda" if available, otherwise "cpu".
        """
        self.device = device
        self.processor = AutoProcessor.from_pretrained("suno/bark-small")
        self.model = BarkModel.from_pretrained("suno/bark-small")
        self.model.to(self.device)

    def synthesize(self, text: str, voice_preset: str = "v2/en_speaker_1"):
        """
        Synthesizes audio from the given text using the specified voice preset.
        Args:
            text (str): The input text to be synthesized.
            voice_preset (str, optional): The voice preset to be used for the synthesis. Defaults to "v2/en_speaker_1".
        Returns:
            tuple: A tuple containing the sample rate and the generated audio array.
        """
        inputs = self.processor(text, voice_preset=voice_preset, return_tensors="pt")
        inputs = {k: v.to(self.device) for k, v in inputs.items()}

        with torch.no_grad():
            audio_array = self.model.generate(**inputs, pad_token_id=10000)

        audio_array = audio_array.cpu().numpy().squeeze()
        sample_rate = self.model.generation_config.sample_rate
        return sample_rate, audio_array

    def long_form_synthesize(self, text: str, voice_preset: str = "v2/en_speaker_1"):
        """
        Synthesizes audio from the given long-form text using the specified voice preset.
        Args:
            text (str): The input text to be synthesized.
            voice_preset (str, optional): The voice preset to be used for the synthesis. Defaults to "v2/en_speaker_1".
        Returns:
            tuple: A tuple containing the sample rate and the generated audio array.
        """
        pieces = []
        sentences = nltk.sent_tokenize(text)
        silence = np.zeros(int(0.25 * self.model.generation_config.sample_rate))

        for sent in sentences:
            sample_rate, audio_array = self.synthesize(sent, voice_preset)
            pieces += [audio_array, silence.copy()]

        return self.model.generation_config.sample_rate, np.concatenate(pieces) : The class takes an optional parameter, which specifies the device to be used for the model (either if a GPU is available, or ). It loads the Bark model and the corresponding processor from the pre-trained model. You can also use the large version by specifying for the model loader. Initialization ( __init__ ) device cuda cpu suno/bark-small suno/bark : This method takes a input and a parameter, which specifies the voice to be used for the synthesis. You can check out other value . It uses the to prepare the input text and the voice preset, and then generates the audio array using the method. The generated audio array is converted to a NumPy array and the sample rate is returned along with the audio array. Synthesize ( synthesize ) text voice_preset voice_preset here processor model.generate() : This method is used for synthesizing longer text inputs. It first tokenizes the input text into sentences using the function. For each sentence, it calls the method to generate the audio array. It then concatenates the generated audio arrays, with a short silence (0.25 seconds) added between each sentence. Long-form Synthesize ( long_form_synthesize ) nltk.sent_tokenize synthesize Now that we have the set up, we need to prepare the Ollama server for the large language model (LLM) serving. To do this, you'll need to follow these steps: TextToSpeechService : Run the following command to download the latest Llama-2 model from the Ollama repository: Pull the latest Llama-2 model ollama pull llama2 . : If the server is not yet started, execute the following command to start it: . Start the Ollama server ollama serve Once you've completed these steps, your application will be able to use the Ollama server and the Llama-2 model to generate responses to user input. Next, we'll move to the main application logic. First, we need to initialize the following components: : We'll use the Rich library to create a better interactive console for the user within the terminal. Rich Console : We'll initialize a Whisper speech recognition model which is a state-of-the-art open-source speech recognition system developed by OpenAI. We'll use the base English model ( ) for transcribing user input. Whisper Speech-to-Text base.en : We'll initialize a Bark text-to-speech synthesizer instance, which was implemented above. Bark Text-to-Speech : We'll use the built-in from the Langchain library which provides a template for managing the conversational flow. We'll configure it to use the Llama-2 language model with the Ollama backend. Conversational Chain ConversationalChain import time
import threading
import numpy as np
import whisper
import sounddevice as sd
from queue import Queue
from rich.console import Console
from langchain.memory import ConversationBufferMemory
from langchain.chains import ConversationChain
from langchain.prompts import PromptTemplate
from langchain_community.llms import Ollama
from tts import TextToSpeechService

console = Console()
stt = whisper.load_model("base.en")
tts = TextToSpeechService()

template = """
You are a helpful and friendly AI assistant. You are polite, respectful, and aim to provide concise responses of less 
than 20 words.
The conversation transcript is as follows:
{history}
And here is the user's follow-up: {input}
Your response:
"""
PROMPT = PromptTemplate(input_variables=["history", "input"], template=template)
chain = ConversationChain(
    prompt=PROMPT,
    verbose=False,
    memory=ConversationBufferMemory(ai_prefix="Assistant:"),
    llm=Ollama(),
) Now, let's define the necessary functions: : This function runs in a separate thread to capture audio data from the user's microphone using the . The callback function is called whenever new audio data is available, and it puts the data into a for further processing. record_audio sounddevice.RawInputStream data_queue : This function utilizes the Whisper instance to transcribe the audio data from the into text. transcribe data_queue : This function feeds the current conversation context to the Llama-2 language model (via the Langchain ) and retrieves the generated text response. get_llm_response ConversationalChain : This function takes the audio waveform generated by the Bark text-to-speech engine and plays it back to the user using a sound playback library (e.g., ). play_audio sounddevice def record_audio(stop_event, data_queue):
    """
    Captures audio data from the user's microphone and adds it to a queue for further processing.
    Args:
        stop_event (threading.Event): An event that, when set, signals the function to stop recording.
        data_queue (queue.Queue): A queue to which the recorded audio data will be added.
    Returns:
        None
    """
    def callback(indata, frames, time, status):
        if status:
            console.print(status)
        data_queue.put(bytes(indata))

    with sd.RawInputStream(
        samplerate=16000, dtype="int16", channels=1, callback=callback
    ):
        while not stop_event.is_set():
            time.sleep(0.1)

def transcribe(audio_np: np.ndarray) -> str:
    """
    Transcribes the given audio data using the Whisper speech recognition model.
    Args:
        audio_np (numpy.ndarray): The audio data to be transcribed.
    Returns:
        str: The transcribed text.
    """
    result = stt.transcribe(audio_np, fp16=False)  # Set fp16=True if using a GPU
    text = result["text"].strip()
    return text

def get_llm_response(text: str) -> str:
    """
    Generates a response to the given text using the Llama-2 language model.
    Args:
        text (str): The input text to be processed.
    Returns:
        str: The generated response.
    """
    response = chain.predict(input=text)
    if response.startswith("Assistant:"):
        response = response[len("Assistant:") :].strip()
    return response

def play_audio(sample_rate, audio_array):
    """
    Plays the given audio data using the sounddevice library.
    Args:
        sample_rate (int): The sample rate of the audio data.
        audio_array (numpy.ndarray): The audio data to be played.
    Returns:
        None
    """
    sd.play(audio_array, sample_rate)
    sd.wait() Then, we define the main application loop. The main application loop guides the user through the conversational interaction as follows: The user is prompted to press Enter to start recording their input. Once the user presses Enter, the function is called in a separate thread to capture the user's audio input. record_audio When the user presses Enter again to stop the recording, the audio data is transcribed using the function. transcribe The transcribed text is then passed to the function, which generates a response using the Llama-2 language model. get_llm_response The generated response is printed to the console and played back to the user using the function. play_audio if __name__ == "__main__":
    console.print("[cyan]Assistant started! Press Ctrl+C to exit.")

    try:
        while True:
            console.input(
                "Press Enter to start recording, then press Enter again to stop."
            )

            data_queue = Queue()  # type: ignore[var-annotated]
            stop_event = threading.Event()
            recording_thread = threading.Thread(
                target=record_audio,
                args=(stop_event, data_queue),
            )
            recording_thread.start()

            input()
            stop_event.set()
            recording_thread.join()

            audio_data = b"".join(list(data_queue.queue))
            audio_np = (
                np.frombuffer(audio_data, dtype=np.int16).astype(np.float32) / 32768.0
            )

            if audio_np.size > 0:
                with console.status("Transcribing...", spinner="earth"):
                    text = transcribe(audio_np)
                console.print(f"[yellow]You: {text}")

                with console.status("Generating response...", spinner="earth"):
                    response = get_llm_response(text)
                    sample_rate, audio_array = tts.long_form_synthesize(response)

                console.print(f"[cyan]Assistant: {response}")
                play_audio(sample_rate, audio_array)
            else:
                console.print(
                    "[red]No audio recorded. Please ensure your microphone is working."
                )

    except KeyboardInterrupt:
        console.print("\n[red]Exiting...")

    console.print("[blue]Session ended.") Result Once everything is put down together, we can run the application as shown in the video above. The application runs quite slowly on my MacBook because the Bark model is large, even in its smaller version. Therefore, I have slightly sped up the video. For those with a CUDA-enabled computer, it might run faster. Here are the key features of our application: : Users can start and stop recording their voice input, and the assistant responds by playing back the generated audio. Voice-based interaction The assistant maintains the context of the conversation, enabling more coherent and relevant responses. The use of the Llama-2 language model allows the assistant to provide concise and focused responses. Conversational context: For those aiming to elevate this application to a production-ready status, the following enhancements are recommended: : Incorporate optimized versions of the models, such as whisper.cpp, llama.cpp, and bark.cpp, which are designed to boost performance, especially on lower-end computers. Performance Optimization : Implement a system that allows users to customize the bot's persona and prompt, enabling the creation of different types of assistants (e.g., personal, professional, or domain-specific). Customizable Bot Prompts : Develop a user-friendly GUI to enhance the overall user experience, making the application more accessible and visually appealing. Graphical User Interface (GUI) : Expand the application to support multimodal interactions, such as the ability to generate and display images, diagrams, or other visual content in addition to the voice-based responses. Multimodal Capabilities Finally, we have completed our simple voice assistant application, full code can be found at: . This combination of speech recognition, language modeling, and text-to-speech technologies demonstrates how we can build something that sounds difficult but can actually run on your computer. Let's enjoy coding, and don't forget to subscribe to so you don't miss the latest in AI and programming articles. https://github.com/vndee/local-talking-llm my blog Also published here

How to Build Your Own Voice Assistant and Run it Locally Using Whisper + Ollama + Bark

কীভাবে আপনার নিজের ভয়েস সহকারী তৈরি করবেন এবং হুইস্পার + ওল্লামা + বার্ক ব্যবহার করে স্থানীয়ভাবে এটি চালাবেন

So erstellen Sie Ihren eigenen Sprachassistenten und führen ihn lokal mit Whisper + Ollama + Bark aus

Cómo crear su propio asistente de voz y ejecutarlo localmente usando Whisper + Ollama + Bark

Comment créer votre propre assistant vocal et l'exécuter localement à l'aide de Whisper + Ollama + Bark

अपना खुद का वॉयस असिस्टेंट कैसे बनाएं और इसे व्हिस्पर + ओलामा + बार्क का उपयोग करके स्थानीय रूप से कैसे चलाएं

独自の音声アシスタントを構築し、Whisper + Ollama + Bark を使用してローカルで実行する方法

나만의 음성 어시스턴트를 구축하고 Whisper + Ollama + Bark를 사용하여 로컬에서 실행하는 방법

Como construir seu próprio assistente de voz e executá-lo localmente usando Whisper + Ollama + Bark

Как создать собственный голосовой помощник и запустить его локально с помощью Whisper + Ollama + Bark

Kendi Sesli Asistanınızı Oluşturma ve Whisper + Ollama + Bark Kullanarak Yerel Olarak Çalıştırma

Cách xây dựng trợ lý giọng nói của riêng bạn và chạy nó cục bộ bằng Whisper + Ollama + Bark

如何构建您自己的语音助手并使用 Whisper + Ollama + Bark 在本地运行

Hi There! I think that every developer who transitions to a team leader role initially strives to return to coding and solving tasks alongside the team. Later on, we start to encompass more business tasks and issues, diving into business-related challenges, communication between departments or clients, and architecture. From this point on, we no longer have either the time or the desire to do something else. A typical team lead's calendar begins to resemble this: How Do I Return to Development and Start Coding Again? Where Should I Begin? It's also important to assess how genuinely busy you are and what your typical workday looks like. Do you engage in self-improvement after work or not? These are all crucial factors. Based on my experience, I suggest taking steps along the path from “no time before or after work, no desire or opportunity” to “I'm always at the computer, and this is my passion.” Block Your Time! An effective starting point is to schedule dedicated time for development. Simply block out 'coding time' in your calendar for an hour or more. If possible, consider reserving half a day or a full day each week specifically for tackling technical tasks. Yes, it might involve moving meetings around, eliminating unnecessary ones, or discussing the necessity of attending some of them. However, consider reassessing whether certain grooming sessions are still relevant for you. Perhaps you're spending an hour there without much impact? Redirect that time towards coding! Code Review With Your Team! The second and most crucial aspect for optimizing certain processes around you is to communicate the project's values or approaches to your colleagues. Not every developer sees the same approach to problem-solving, so it's essential to predefine coding styles, test coverage, and the fundamental methods and mechanics of the platform or services separately. Always conduct code reviews, and if there's a sense that a question is dragging on, gather the team to swiftly address issues in the pull requests (PRs). As practice shows, this approach speeds up issue resolution time, consequently improving the time to market for features. Over time, your team will fully understand and apply development approaches that require less attention. You'll be focused solely on solving the task at hand and its logic, which will save a few minutes initially and, in the long run, potentially hours of development time. What Are You Responsible For? It might not seem like the most obvious task, but ask yourself, what are you responsible for? What do you need to do? Write down all these points on a sheet of paper and see if you've taken on anything unnecessary. Perhaps you're doing someone else's work just because it has become a habit. Maybe you've been helping a neighboring team with their processes, and you're still involved. Clearly define your position and what you contribute to the project or the company. If you lead a large team, use notes where you can create a queue of tasks and issues. Always conduct reviews, and ensure that if you're a DevOps lead, for example, you aren't inadvertently handling tasks meant for mobile app developers. If you find yourself overloaded with tasks and dependencies, it's worth stopping to talk to your superiors and figure out why this is happening in your department. For example, if you're a DevOps team responsible for Data Engineers, and they have their own lead, it might make sense to delegate responsibilities back to their lead instead of your department. Create specifications and necessary documents to formalize agreements or any hidden details about setup or maintenance and return people to their respective teams. It's essential to note that this is just an example, and everyone has their own teams and principles of their formation. Prioritization and Delegation It's possible that you're not getting things done because priorities keep shifting. The entire company operates on two-week sprints, but this setup no longer suits you, and you don't see value in it. Features aren't making it to completion within a sprint due to weak priorities. This is relevant for service-oriented teams. Consider exploring Kanban or a waterflow approach. Our teams are like separate islands where we have the right to try changing processes for the better. Test transitioning to the new approach for a month, and observe your metrics. In my experience, a couple of weeks were enough to notice that Scrum wasn't suitable for us, and we switched to Kanban. Next, try breaking down the team into domain zones, but not too granularly. Immerse each team member following the 70/30 rule: 70% dedicated to their main stack, project, or product 30% for everything else If your team has more than 5 people, you'll cover all services and functions, allowing individuals to dive faster into the subject area. What does this achieve? It allows you to delegate some tasks to the team rather than doing everything yourself if you see that a developer already has a good understanding and immersion. You don't need to describe the entire algorithm and integrations! They already know it all! Time Management and Productivity How Is the Team Planning Its Work Time? Let's start with something simple: how do you operate as a team? Take a look at your estimations and how you assess tasks. Is everything in order? Perhaps there's room for improvement or the introduction of a workload coefficient? The workload coefficient helps understand how each team member is loaded during a sprint or week, considering potential distractions for support. For instance, if you're a service team with your own product to maintain, other teams might seek your assistance or request enhancements, leading to time spent on communication within the sprint. The same goes for dealing with bugs; you might frequently get sidetracked to address urgent issues in the production environment. But that's a separate topic, and I'd advise checking out my previous article on how to make gradual improvements in this area. https://hackernoon.com/just-go-ahead-and-test-your-project-part-1?embedable=true Now, back to the coefficient. If we acknowledge that each of us is called to a chat or a meeting at least 1 day out of 5 to resolve an issue, take that into during planning. This way, you'll realistically manage to accomplish tasks that truly benefit the team, potentially freeing up time to write code. Try the Pomodoro technique. Nothing groundbreaking; just use an app on your phone that allows you to focus on a task for a set time interval, like 45 minutes. Nothing special, I guess. Utilize trackers. Conduct an investigation into what you spend your 8 working hours on — record each hour and minute of your activities during the week or month. You might discover factors that distract you, or you might notice that taking a 15-minute walk after lunch makes you work more efficiently—perhaps that's the key to success? Or, if you have three consecutive meetings, do you find yourself doing nothing for an hour afterward, just reading specifications? Maybe it's challenging for you? The point is to scrutinize what you're doing, and I believe you'll identify areas for improvement. Participation in Technically Challenging Projects If you find yourself unable to attend meetings dedicated to system design or architectural solutions, read follow-ups or documentation. Try to understand how and what solves the problem. It's preferable not to miss such meetings and strive to immerse yourself as much as possible in the technical aspects. Select projects or project aspects that require a deep dive into the code. This will help you stay abreast of new technologies and development methodologies. RnD for You If you notice areas in the project that have issues or where functionality could be improved, feel free to create prototypes. This will not only allow you to visualize the proposed changes but also provide the team with tangible material for discussion and decision-making. The main goal is not just to showcase ideas but to implement them into the project if they prove to be genuinely significant or beneficial. For example, if you've always dreamt of migrating outdated services from Java 1.8 to version 21, why not give it a try? Create a prototype, show it to the team, develop your solution, and thoroughly document the entire process for future reference. This approach helps not only to implement technical improvements but also to create a shared understanding within the team regarding potential changes. Thus, you can make a constructive contribution to the project, ensuring its effective development and fostering innovation. Review Point! At this stage, you'll have a couple of hours to write code, propose solutions, and then you can take a breather. Of course, the leadership position simply won't allow you to do both, and if your focus is still on development, it might be worth considering a return. There's nothing wrong with that—realizing that management is becoming dull for you, even if you excel at it, is okay. It's just that, at this point in time, it has lost its appeal for you. If You Still Have Some Free Time Learning and Self-Development Continuously educate yourself by reading technical literature, exploring educational courses, and participating in technical conferences. This will help you stay abreast of the latest trends and best practices in software development. Reading technical literature provides a unique opportunity to delve into the depths of new technologies, methodologies, and best practices. This can include books, articles, blogs, and other materials covering various aspects of software development. Taking educational courses is a structured and systematic way to acquire knowledge on new topics and technologies. Online course platforms offer a wide range of courses on different programming languages, frameworks, and concepts. Participating in technical conferences opens up the opportunity not only to learn about the latest trends and innovations but also to engage with industry professionals. Conferences provide a platform for sharing experiences, discussing challenging issues, and building connections within the technical community. In summary, continuous learning through reading, taking courses, and attending conferences allows software developers not only to keep up with the latest trends but also to actively integrate new knowledge and skills into their daily work. Examples: leetcode, Udemy, or Youtube (sometimes, we can find really good FREE content there!). Working on Personal Projects If possible, work on personal projects in your free time. This will not only enhance your programming skills but also serve as a source of new ideas for your primary job. Additionally, combining this activity with the RnD point from the article can be an extra incentive for creativity and innovation. Working on personal projects allows you to apply your skills in practical scenarios, experiment with new technologies, and solve real-world problems. These projects may involve developing your own web applications, creating open-source projects, or participating in interesting side projects. Integrating this activity with the research and development (RnD) work mentioned earlier enables you to create prototypes and showcase them at your workplace. Opening your project to the public, such as participating in open-source development, not only improves your skills but also contributes to building valuable professional connections and gaining recognition for your creativity. However, it is crucial to remember that adhering to the confidentiality policy (NDA) of your main job is a priority. Before embarking on personal projects, it is advisable to consult with legal professionals and management to ensure that your creative process does not violate established rules and to facilitate the free development of your creative energy while preserving the confidentiality of sensitive data. Conclusion Finding time for coding as a team leader requires conscious effort and effective priority management. Remember that your role involves not only directly leading the team but also maintaining your technical skills at a satisfactory level. It will be challenging, and I wish you the best of luck! I saw the problem a long time ago. If you'd like to read professional books, I’d recommend you read books: link and link

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NDAX

ndax.io

11-50 employees

Since 2018

COMPANY RANKING

NDAX

EVERGREEN INDEX #7400

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