Compra Rápida is checkout made easy. We bring a local and mobile-first purchase experience through a 1-click checkout, making it easier for merchants to sell and consumers to buy online.

Compra Rápida

Things To Think About When Securing Your Bitcoin

Você deve gastar em média 5 minutos para ler esse texto. Seria necessário lê-lo 1440 vezes até o seu produto comprado online chegar, se não houver atrasos, claro. Muni Perez é um dos muitos brasileiros que gostam de comprar pela internet. De férias nos Estados Unidos, ele percebeu a diferença em relação às entregas das compras online que realizou na terra do Tio Sam com as que são feitas no Brasil. Se você é um dos que não resiste ao carrinho de compras virtual, você precisa entender do que estamos falando. “Se você está lendo esta história, provavelmente gosta de computadores e curte compras online.” “No Brasil, as pessoas também amam compras online e o e-commerce está crescendo exponencialmente. No entanto, cada compra feita cria uma dor de cabeça — o frete. Se você vive nos Estados Unidos, provavelmente, está acostumado a pagar 4 ou 5 dólares pelo frete na Amazon e receber seus produtos em poucos dias. Claro, isso depende da disponibilidade do item, mas em geral, a Amazon tem estoque e preparo para te entregar rapidamente. No Brasil é um pouco diferente. Primeiro, você não tem muitas opções de companhias para transportar seus produtos, onde cada uma teria que competir para ganhar seu coração. A parte boa da competição é que geralmente os preços diminuem e os serviços melhoram. Existe apenas uma grande — e não muito competente — companhia estatal e algumas companhias privadas que possuem contratos com grandes sites de e-commerce. Como resultado, quando você compra um produto online no Brasil, seu frete pode custar mais que o próprio produto e pode ou não ser entregue (Sim! Isso acontece). O frete muitas vezes é bastante demorado, seu produto pode levar semanas para chegar, dependendo de onde você mora, e às vezes ele é roubado da grande companhia estatal de transporte (chamada Correios) — sim, isso acontece, de verdade. Eu estou atualmente de férias nos Estados Unidos e há poucos dias precisei de uma nova tela protetora para meu novo iPhone. Entrei no site da Amazon, escolhi entre uma enorme variedade de protetores de tela e consegui uma por 9 dólares. Quando prosegui para os detalhes da compra, fiquei surpreso com as opções de frete — o que me inspirou a escrever este texto. Veja por você mesmo: Sim! Levariam dois dias e seria entregue num domingo — de graça. É importante ressaltar que minha conta é Amazon Prime, mas ainda assim, acho que é totalmente válido pagar $8,25 por mês se você faz muitas compras. Então, para ter uma comparação justa voltei à Amazon com uma conta comum, não uma conta Prime e tentei comprar o mesmo item. O transporte padrão foi quase o preço do produto, porque o produto é realmente barato: Então, 9 dólares pelo produto, 6 dólares pelo frete e demoraria cerca de uma semana para ser entregue. Ainda assim, ótimo. Aí entrei num dos maiores varejistas e portais e-commerce do Brasil, Americanas.com. Primeiro eu procurei apenas por película protetora. Veja o que encontrei como frete: Sim! O produto custa 20 reais, o frete custa R$13,31 e demoraria 9 dias úteis para chegar. Obs: Quando comparando as moedas, você pode se imaginar pagando 20 dólares por uma película protetora, ao invés de pagar 20 reais. Se você realmente converter reais para dólares americanos seria um preço bem baixo, mas a renda média em reais é menor que a em dólares americanos. Portanto, considere que você pagaria 20 dólares por um item e 13 dólares pelo frete. Ok, de volta à história. Até agora os preços são absurdamente mais altos no Brasil, mas fala sério, é apenas um produto barato. Vamos ver o que acontece quando você quer comprar um celular (que é absurdamente mais caro também): Ok, agora eu desisto. O frete é na verdade MUITO mais caro e demoram 13 dias úteis para chegar, ou seja, você tem que esperar cerca de 3 semanas — se for sortudo. Sobre as moedas novamente, se imagine pagando 700 dólares num Moto G 8GB 2Gen. Para ser honesto, voltei na Amazon e simulei um pedido do mesmo Moto G junto com a tela protetora para meu iPhone, SEM a conta Prime. Surpresa: Frete grátis e demoram de 5 a 8 dias úteis, o telefone era muito mais barato mesmo se eu tivesse convertido as moedas. Oh My God! Ainda bem que tem luz no fim do túnel, mesmo que seja fraca, como algumas startups que começam a mostrar uma tentativa de solucionar esse gigante e absurdo problema logístico no meu país. Um exemplo incrível é a , que até mesmo recebeu uma carta da grande companhia estatal, dizendo que eles estavam quebrando a lei porque os Correios possuem o monopólio de correspondência. Ok, agora eu desisti.” Shippify , desiste não! Muni Perez Estamos aqui justamente para resolver esse problema, pois acreditamos que é possível sim proporcionar uma melhor experiência de entrega a todos. :D História original disponível . aqui Curta a nossa página no e nos siga no e no . Facebook Twitter Instagram

Compras online nos EUA vs Brasil

Cosmos, with its visionary mission to create the "Internet of Blockchains," and Kaspa, showcasing a 900x growth with its scalable technology, are significant players in the blockchain space. Amid these advancements, BlockDAG (BDAG) emerged, inspired by Kaspa but with distinct innovation, rapidly raising $3 million in its presale. With a fast-paced development strategy and a user-centric approach, BlockDAG demonstrates significant growth potential and promises substantial returns for early investors. Cosmos (ATOM): The Internet of Blockchains Cosmos (ATOM), renowned for its audacious goal of establishing the "Internet of Blockchains," functions via a cutting-edge protocol that makes communicating easier for various blockchain networks. This feature increases productivity and expands the use cases for decentralized apps (DApps). Its native token, ATOM, is essential to the upkeep and functionality of the Cosmos network. Cosmos' price scalability, environmental friendliness, and constantly expanding network of linked blockchains entice investors. Its relationships and recent enhancements have put it in an excellent position to grow significantly during the next bull market. Kaspa’s 900x Growth Kaspa is a groundbreaking cryptocurrency that is changing the online environment with its decentralized and scalable platform. With cutting-edge technology, Kaspa promises quicker and more effective transaction processing, addressing the scalability problems of its forerunners, such as Bitcoin. Kaspa has grown astronomically despite its youth; in just two years, its value has increased by an incredible 900 times. Its scaling solution, meanwhile, is still in its infancy and faces challenges in garnering broad acceptance and dispelling skepticism within the cryptocurrency community. BlockDAG: The Best Cryptocurrency Altcoin to Buy in 2024 BlockDAG (BDAG), an innovative Proof-of-Work initiative inspired by the Kaspa protocol, has garnered considerable attention in the crypto community, successfully raising $3 million during its second presale batch. With ambitious targets to secure $600 million by the end of 2024, BlockDAG demonstrates a strong commitment to growth. Furthermore, BlockDAG stands out for its rapid development pace, planning to debut its mainnet within six months—a notable achievement in an industry where such developments typically span years. The project emphasizes user-friendliness and sustainability, featuring energy-efficient mining equipment and a mobile mining app that conserves battery life. For early investors, the prospects are particularly promising; purchasing BDAG now could lead to a remarkable 3233% return on investment, considering the presale price of $0.0015 per BDAG is significantly lower than the launch price of $0.05. Buoyed by substantial early funding and investor enthusiasm, BlockDAG is enhancing community engagement with a $2 million mega giveaway for 50 lucky participants. Key Takeaways While Cosmos and Kaspa are making impressive strides in enhancing blockchain interoperability and scalability, BlockDAG is carving out its niche with remarkable speed and innovation. By securing substantial funds early on and setting ambitious targets, BlockDAG is not just keeping pace but setting new benchmarks in the blockchain industry. Its commitment to user-friendliness, energy efficiency, and rapid development, coupled with the enticing potential for high returns on investment, positions BlockDAG as a compelling choice for those looking to engage with the future of cryptocurrency. Invest In BlockDAG Today | | | Website Presale Telegram Discord This story was distributed as a release by BTCWire under HackerNoon’s Business Blogging Program. Learn more about the program here: https://business.hackernoon.com/

Top Crypto To Buy This Month: BlockDAG's Presale Hits $3M, Challenging Kaspa Amid Cosmos' ATOM Rise

এই মাসে কেনার জন্য শীর্ষ ক্রিপ্টো: BlockDAG-এর প্রিসেল $3M হিট, কসমসের ATOM উত্থানের মধ্যে Kaspa চ্যালেঞ্জিং

Top-Kryptowährung zum Kauf in diesem Monat: Der Vorverkauf von BlockDAG erreicht 3 Millionen US-Dollar und fordert Kaspa inmitten des ATOM-Aufstiegs von Cosmos heraus

Principales criptomonedas para comprar este mes: la preventa de BlockDAG alcanza los $ 3 millones, desafiando a Kaspa en medio del aumento de ATOM de Cosmos

Meilleure crypto à acheter ce mois-ci : la prévente de BlockDAG atteint 3 millions de dollars, défiant Kaspa au milieu de la montée en puissance d'ATOM de Cosmos

इस महीने खरीदने के लिए शीर्ष क्रिप्टो: ब्लॉकडीएजी की प्रीसेल $3 मिलियन तक पहुंच गई, जो कॉसमॉस के एटम उदय के बीच कास्पा को चुनौती दे रही है

今月購入すべきトップ仮想通貨：BlockDAGのプレセールは300万ドルに達し、CosmosのATOM上昇の中でKaspaに挑戦

이번 달 구매할 최고의 암호화폐: BlockDAG의 사전 판매가 300만 달러를 달성하여 Cosmos의 ATOM 상승 속에서 Kaspa에 도전

Principais criptomoedas para comprar este mês: pré-venda do BlockDAG atinge US$ 3 milhões, desafiando Kaspa em meio ao aumento do ATOM do Cosmos

Лучшая криптовалюта для покупки в этом месяце: предварительная продажа BlockDAG достигла 3 миллионов долларов, бросая вызов Kaspa на фоне роста ATOM Cosmos

Bu Ay Satın Alınacak En İyi Kripto: BlockDAG'ın Ön Satışı 3 Milyon Dolara Ulaştı ve Cosmos'un ATOM Yükselişinde Kaspa'ya Zorluk Çekti

Tiền điện tử hàng đầu nên mua trong tháng này: Đợt bán trước của BlockDAG đạt 3 triệu USD, thách thức Kaspa trong bối cảnh ATOM của Cosmos trỗi dậy

本月最值得购买的加密货币：BlockDAG 预售达到 300 万美元，在 Cosmos ATOM 崛起之际挑战 Kaspa

231 Stories To Learn About Blockchain Writing Contest

The initial launch of ChatGPT just one year ago paved the way for a generative AI boom that’s continued to captivate a vast array of industries around the world. With more firms seeking to embrace this next generation of , some market commentators are gaining a sense of . AI déjà vu This widespread clamoring to draws parallels to the dotcom boom at the turn of the 21st Century. With ChatGPT users recently dropping for the , should we be wary of a bubble that could be destined to burst? embrace generative AI third consecutive month "I think this will be the biggest bubble of all time," , CEO of Stability AI. "I call it the 'dot AI' bubble, and it hasn't even started yet." warned Emad Mostaque \Mostaque’s views were echoed by James Penny, Chief Investment Officer of TAM Asset Management, in a recent Bloomberg interview. " " . Companies that even mention the word AI in their earnings are seeing boosts to their share price, and that smells very much like the dot-com era, Penny explained Generative AI has certainly become the word of the year in terms of emerging technology, and stocks that possess varying forms of AI exposure have experienced significant growth throughout 2023. One of the biggest beneficiaries of the rise of generative AI on Wall Street has been NVIDIA, which recently attained a market capitalization of , recording almost 200% growth throughout the first three quarters of 2023 alone. over $1 trillion “The company is growing rapidly and is well-positioned to benefit from the development of artificial intelligence (AI), metaverse, and other new technologies,” explains Maxim Manturov, head of investment research at . Freedom Finance Europe “ ” Manturov added. Factors such as generative artificial intelligence and the metaverse may provide NVIDIA with a FAANG level of popularity. Generative artificial intelligence is a rapidly growing field that has the potential to revolutionize many industries, As well as its position as a market leader in providing the hardware that can power generative AI services, NVIDIA also moved quickly in embracing the technology. In March 2023, the company providing businesses with the resources to ‘build refine and operate custom large language models and generative AI models.’ announced a set of cloud services So, should NVIDIA and Wall Street’s other key players fear an AI bubble that’s destined to burst? Evidence suggests that the rise of generative AI could be powerful enough to transcend the hype of the dot-com bubble. Tangible Signs of Growth While the dotcom boom saw hype swell to the point where stock values became no longer sustainable, there’s much about the excitement for AI that appears to be far more tangible. Crucially, circumstances surrounding tech markets are fundamentally different from the turn of the century, and many Wall Street firms have been reacting to widespread investor sell-offs throughout 2022, punctuated by high inflation and rising interest rates. As Financial Times columnist , “ ” John Plender notes applying a higher discount rate to distant future cash flows in the tech sector shrank the present value of those cash flows. This year’s bounce, far from being driven by central banks, reflects something real. The potential of generative AI could transform how the economy works on a fundamental level, which can see significant and positive change throughout a vast range of industries that transcends the potential of the dotcom boom some 25 years ago, with more . people investing in it According to investment advisory firm , comparisons between the current market and the dotcom boom ignore the underlying data points that can indicate that a bubble is emerging. Roundhill Investments The firm’s analysis of key factors that can indicate a bubble, such as the emergence of irrational exuberance, high valuation, weak stock fundamentals, growing IPO volumes, and the rise of baseless market narratives suggests that a bubble for generative AI is not currently in play. Although this doesn’t necessarily mean that generative AI is immune to becoming a bubble in the future, we’re seeing many signs of tangible growth and industry adoption that point to a technology that has the power to disrupt the vast majority of sectors. The Rise and Rise of Generative AI Use Cases The clearest sign that isn’t in a bubble can be found in its rapidly growing set of use cases across different industries. generative AI Recently, system software firm Workday announced that it will be launching its own AI marketplace in the first half of 2024, with partners like BetterUp, Paradox, Hiredscore, Techwolf, Accenture, and Amazon already signed up. “ ” , Workday’s co-founder and co-CEO. The Workday AI Marketplace will enable our customers to harness the incredible amount of AI innovation happening today while at the same time give them the peace of mind in knowing that each solution is proven, trusted, and meets Workday’s stringent standards for responsible AI, said Aneel Bhusri “ ” Combining the power of the Workday platform with some of the world’s most innovative AI native companies will give our customers a running start in building for the future. Just two days prior to Workday’s announcement came a similar news story from another software firm, SAP. Rather than an AI marketplace, SAP opted to utilize generative AI to develop a Joule, natural-language co-pilot that’s designed to provide rich contextualized insights for businesses. “ ” . “Joule delivers on SAP’s proven track record of revolutionary technology that drives real results.” By quickly sorting through and contextualizing data from multiple systems to surface smarter insights, Joule helps people get work done faster and drive better business outcomes in a secure, compliant way, explained a SAP press release Generative AI has even provided fresh opportunities in the world of social media, offering and generative AI stickers on Meta’s messaging apps that have the power to . intelligent image editing on Instagram create images based on textual cues These generative AI use cases illustrate that the technology isn’t just helping businesses modernize their processes; it’s showing that AI is adaptable enough to provide bespoke solutions to companies regardless of their sector or USP. It’s this flexibility and adaptability that makes generative AI a technological proposition without precedence. Finding Sustainability in an Ageing Workforce In a into the emergence of AI technology, it’s suggested that the adoption of AI has come at an opportune time in nations like the United Kingdom, which has recorded an increasingly older workforce since 2020, with 10-year projections pointing to a growing trend. recent Barclays report Although there is plenty of fear among workers that generative AI may soon become intelligent enough to replace them entirely, it’s worth considering that artificial intelligence can be a sustainable solution in maintaining productivity for businesses that are seeing more employees reach retirement age without a large enough talent pool to recruit a replacement. This makes AI’s rising use cases not only transformative but essential for businesses worldwide seeking productivity enhancements. AI’s Big Bang While falling numbers of ChatGPT users are worth monitoring, it’s more likely a sign of a maturing AI market. For many months, ChatGPT was the star of the generative AI boom, and its ability to generate richly detailed and accurate content from simple prompts provided a crucial novelty factor among curious users. Now, is beginning to permeate the world around us less than a year on from ChatGPT’s initial launch, this new technological frontier is less of a novelty and more of a necessity for growth. as generative AI With more varied and bespoke use cases emerging on quite literally a daily basis, the generative AI boom is shaping up to be more of a big bang and is more likely to complement future technological developments like 5G and the metaverse rather than be replaced by them. While the danger of market hype can always lead to inflated prices, it’s clear that generative AI is a rare transformative technology that’s likely to change the world. With this in mind, the available evidence points to more of a boom than a bust.

Backing the Boom: Why the Rise of Generative AI is Nothing Like the Dotcom Bubble

Respaldando el auge: por qué el auge de la IA generativa no se parece en nada a la burbuja de las puntocom

Soutenir le boom : pourquoi l’essor de l’IA générative n’a rien à voir avec la bulle Internet

बूम का समर्थन: क्यों जनरेटिव एआई का उदय डॉटकॉम बबल जैसा कुछ नहीं है

ブームを後押しする: 生成 AI の台頭がドットコム バブルのようなものではない理由

Apoiando o boom: por que a ascensão da IA generativa não se parece em nada com a bolha pontocom

Ủng hộ sự bùng nổ: Tại sao sự trỗi dậy của AI sáng tạo không giống bong bóng Dotcom

支持繁荣：为什么生成式人工智能的兴起与互联网泡沫完全不同

As an AI startup founder, you likely know how impactful large language models like ChatGPT have been in advancing conversational AI. However, with commercial licensing costs, censorship issues, degraded performance, privacy concerns, and black boxes, these proprietary models remain out of reach for many startups. This is where an open-source project called Vicuna comes in. Developed by a team of researchers from institutions like Stanford, Vicuna is conversational model achieving over 90% of ChatGPT's quality. This makes it an exciting alternative to closed-off models like GPT-4. an open-source Subscribe or follow me on Twitter for more content like this! In this article, we'll explore what Vicuna is, how it works, its capabilities, and how you may be able to leverage it as an AI founder. We'll see how it stacks up to competitors like ChatGPT and the base LLaMA model. I'll also share some helpful tips and guides you can follow for more information about specific aspects of the model. We will concentrate on Vicuna-13b for this article, but there are many different-sized models of Vicuna out there for you to try. Let's begin! Note: Vicuna isn't the only model out there to fine-tune LLaMA for chat. Check out our guides on using , LLaMA v2 , and Alpaca LLaMA-v2-chat for conversational applications. An Overview of Vicuna In the world of conversational AI, we've seen astounding progress recently with models like ChatGPT demonstrating remarkable natural language abilities. However, as a proprietary model with all the issues described above, ChatGPT remains a bad option for many developers. So there's a need for more accessible and open models that can empower innovation in conversational apps. This is where Vicuna comes in. Developed by researchers like Stanford, Berkeley, and MBZUAI, Vicuna represents cutting-edge open conversational AI. from leading institutions It was created by fine-tuning the LLaMA model on curated dialog data, demonstrating the power of transfer learning from an open-source foundation model. Despite being smaller in size than ChatGPT, Vicuna matches its conversational quality and significantly outperforms other open models. But it's not just about the technology with Vicuna. What makes it truly impactful is its availability under a non-commercial research license. This opens up access to state-of-the-art conversational AI that was previously restricted to only large tech companies. We finally have an open model that can power the next generation of chatbots, virtual assistants, conversational search engines, and other innovative applications. Vicuna's promise has already been demonstrated through cool projects that leverage it. For example, used Vicuna to build an intelligent virtual assistant, created a conversational search engine with it, and taps Vicuna's abilities for natural language content creation. MiniGPT4 LLaVA ToolLLaMA And, of course, you may add your own project to this list one day! For AI developers and startups, Vicuna represents an exciting new opportunity. Its high capability, free availability, and permissive research license enable rapid prototyping of conversational apps. Instead of being gated by access to proprietary models, startups can now validate and build products with cutting-edge conversational AI. The playing field just got leveled. So, in summary, Vicuna promises to democratize access to top-tier conversational intelligence. Its emergence represents an important milestone in making open AI models that empower innovation. For any startup looking to leverage conversational AI, Vicuna is definitely a project worth paying attention to! How Was Vicuna Created? What Makes It Special? The story of Vicuna begins with LLaMA, an open-source language model developed by Meta AI. While capable, LLaMA had no inherent conversational abilities, focusing mainly on language itself rather than the art of conversation. Researchers from institutions including Stanford, Berkeley, and MBZUAI set out to change this. Their goal was to create an open-source conversational model rivaling proprietary chatbots like ChatGPT. By the way, what's the difference between an AI model trained to process and analyze text (like LLaMA) versus one specialized for chat (like Vicuna)? There are a few key factors that differentiate the two: - Conversational models like Vicuna have an encoder-decoder structure optimized for dialog. The encoder contextualizes the conversation history and current user input. The decoder then generates a relevant response. General language models like LLaMA lack this specialized architecture. Architecture - Models like Vicuna are fine-tuned to maximize performance specifically on conversational tasks. This involves training on dialog datasets to optimize conversational metrics. LLaMA is trained more generally for text, not specialized for dialog. Training Objective - Conversational models need to handle multi-turn conversations, maintaining context and coherency across multiple exchanges. General text models evaluate one input at a time. Multi-Turn Capabilities - Conversational AI needs to fluidly interact with users, responding to follow-up questions and clarifications. Text evaluation is more passive, lacking user interactivity. Interactivity - Conversational models require more complex evaluation beyond text metrics, testing qualities like consistency, nuance, and the ability to gracefully handle inappropriate responses. Evaluation Whereas a general language model like LLaMA focuses more on textual analysis and generation, without the requirements specific to dialog agents, the goal of conversational AI is fundamentally more complex than passive text evaluation. To that end, the researchers who created Vicuna fine-tuned LLaMA on over 70,000 human-ChatGPT dialog exchanges, specializing the model for conversation and teaching it the natural characteristics of text in conversational contexts. This fine-tuning was crucial for giving their version of LLaMA the conversational intelligence it previously lacked. Through iterative training on the dialog data, LLaMA was transformed into Vicuna, an encoder-decoder transformer optimized for multi-turn conversations. How well did their efforts work? Into the Arena: Evaluating Vicuna Against Alternative Chat AI Models To evaluate Vicuna's capabilities, the researchers tested it on 200 diverse conversational prompts. For further assessment, they had the GPT-4 model comparatively judge Vicuna's responses. The results demonstrated that Vicuna achieved over 90% of ChatGPT's quality in conversational ability, despite being smaller in size. It significantly outperformed the original LLaMA model. By combining architecture optimizations with specialized fine-tuning on human dialog data, the researchers successfully enhanced LLaMA into an open-source conversational model on par with proprietary chatbots. Let's take a look at a head-to-head test as an example, taken from the . official project site Example head-to-head challenge between Vicuna and competitor models, in this case, using ChatGPT-3.5 as a potential alternative. The project site has a collection of example tasks, in which both Vicuna-13b and competing models are asked to go head-to-head. The GPT-4 model is then used as a judge to score each model and state its reasoning. This produces some really eye-opening comparisons. One example is provided in the image above. Another is this challenge, shown below: Roleplay Category: How would you introduce yourself as a medieval knight at a royal banquet? Question: LLaMA-13b's response: "I am a valiant knight, loyal to the king. I will do my utmost to defend his honor and protect his country. (Lame! Scored 7/10 by GPT-4, very generous in my opinion.)" Vicuna-13b: **"**As a medieval knight, I would introduce myself at a royal banquet with a deep bow and a respectful speech, acknowledging my humble origins and my loyalty to the crown. I would say something like: "My lords and ladies, I am a humble knight, sworn to serve and protect the realm. I come from a long line of warriors who have fought to defend this kingdom for generations. I am honored to be here today, in the presence of such esteemed company, and I hope to earn your trust and respect with my deeds and actions. I pledge my sword, my shield, and my life to the service of my king and my people." I would then take my seat at the banquet, ready to listen and learn from the wise counsel of my betters, and to serve them in any way I can." Woah! Way better response from Vicuna. Here's GPT-4's reasoning explaining what makes Vicuna a superior alternative to LLaMA. provided a brief and relevant response, but it lacked the detail and formality expected in a medieval knight's introduction. , on the other hand, offered a more comprehensive and well-structured response, including a respectful speech that showcased the knight's humility, loyalty, and dedication to the kingdom. This response was more fitting for the context of a royal banquet and demonstrated a better understanding of the medieval knight's role and etiquette. Assistant 1 [LLaMA] Assistant 2 [Vicuna] While LLMs are not infallible judges of other LLMs, neither are humans. I think the use of AI to judge and evaluate AI is a pretty scalable and consistent way to adjudicate which alternatives are the best. You should check out some of the other competitor answers and tasks on the . LMSYS.org site Let's Try It Ourselves: How to Build a Basic Chatbot With Vicuna Now that we've seen how the model stacks up against some alternatives, let's see how we can build a simple chatbot that we can interact with from our command line. The steps in the guide provided here can be further expanded so you can keep going and build your own chatbot for your AI project! Step 1: Setup : Make sure is installed on your system. Install Node.js Node.js : Run the following in your terminal: Create a Project Directory mkdir my-chatbot
cd my-chatbot
npm init -y
npm install replicate : Replace with your actual API token: Set Your API Token your_api_token_here export REPLICATE_API_TOKEN=your_api_token_here Step 2: Writing the Chatbot Code Create a file named , and add the following code: chatbot.js const Replicate = require("replicate");

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

async function generateResponse(prompt) {
  const output = await replicate.run(
    "replicate/vicuna-13b:version_hash_here",
    {
      input: { prompt: prompt },
    }
  );
  return output.items[0];
}

const readline = require('readline');
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout
});

function askQuestion() {
  rl.question('You: ', async (userInput) => {
    const botResponse = await generateResponse(userInput);
    console.log(`Bot: ${botResponse}`);
    askQuestion();
  });
}

askQuestion(); Replace with the correct version hash for the Vicuna 13b model. version_hash_here Step 3: Running the Chatbot Run the chatbot by executing: node chatbot.js You can now send a message to your chatbot through the command line! Don't want to build your own chatbot? You can use this demo to assess how Vicuna performs. The includes a couple of demos you can use to play around with the model. Here's an embedded one for you to try (you can also use to access it if it's not available at the link below). model details page for Vicuna-13b-v1.3 this link This demo, build by zeno-ml, lets you compare models and additional parameters to see how well Vicuna performs against competitors like LLaMA, GPT2, and MPT while also varying temperature or other parameters. Vicuna's Limitations While conversational technologies have advanced rapidly, models still face important challenges. Conversational agents lack sufficient grounding in real factual knowledge, making them prone to plausible-sounding but incorrect responses. More grounding in the real world could improve accuracy. One issue is knowledge grounding. Performing logical reasoning, causal inference, and mathematical operations remains difficult for chatbots. Their reasoning capabilities are still limited. Reasoning abilities are another area for improvement. Current solutions like asking a separate AI judge have flaws. Developing rigorous evaluation frameworks is an open problem. Evaluating the conversational quality of AI systems at scale also poses difficulties. Conversational models can sometimes behave inappropriately or unsafely. Better training data curation is important. Additionally, biases and safety issues persist due to reliance on imperfect training data. still proves challenging too. More personalization and customization is needed for different domains. You can't do this out of the box easily. Adapting chatbots to specific users and use cases While great progress has been made, these limitations highlight key areas for improvement. Advancing knowledge grounding, reasoning, evaluation, training data, customization, and deployment efficiency could enable the next level of conversational intelligence with models like Vicuna. Conclusion: Using Vicuna AI as an Open-Source Alternative to ChatGPT, LLaMA, and Other LLMs The development of Vicuna demonstrates promising progress in advancing open-source conversational AI. By fine-tuning the LLaMA model architecture and training methodology specifically for dialog applications, researchers were able to create a freely available conversational agent competitive with leading proprietary alternatives. However, work remains to be done to address limitations around reasoning, evaluation, customization, and other areas. While models like Vicuna achieve strong results on many benchmarks, they do not fully replicate comprehensive human conversation. Ongoing research on aligning these models will be important. Nonetheless, Vicuna represents a valuable step forward in democratizing access to state-of-the-art conversational intelligence. For startups and developers building chatbots, assistants, and other applications, open-source options like Vicuna provide welcome capabilities without restrictive commercial licensing. The origins and technical details behind Vicuna offer useful insights into specialized training approaches for conversational AI. As research continues, we can expect to see further innovations that build on these methods. The authors behind Vicuna have made an important contribution to open-sourcing such a capable dialog agent. While more progress is still needed, Vicuna demonstrates the meaningful results that can come from developing open conversational models. For the AI community, it represents a promising step, not the final destination. With continued work on advancing these technologies, the potential ahead remains exciting. Subscribe or follow me on Twitter for more content like this! Further Reading and Resources You might find these other articles helpful in your quest to build the ultimate chatbot for your new product or project. - An overview of Vicuna with basic model info Vicuna-13b model details - An article on using Vicuna to create chatbots Building chatbots with Vicuna-13B -  A comparison between LLaMA's new version 2 and Vicuna Comparing LLMs for chat: LLaMA v2 vs Vicuna - LangChain is a popular framework for building chat applications LangChain chat models: an overview Also published here

Vicuna: How Does It Compare to Llama, Alpaca, and ChatGPT?

ভিকুনা: এটি লামা, আলপাকা এবং চ্যাটজিপিটির সাথে কীভাবে তুলনা করে?

Vicuna: Wie schneidet es im Vergleich zu Lama, Alpaka und ChatGPT ab?

Vicuña: ¿Cómo se compara con Llama, Alpaca y ChatGPT?

Vicuna : Comment se compare-t-il à Llama, Alpaca et ChatGPT ?

विकुना: इसकी तुलना लामा, अल्पाका और चैटजीपीटी से कैसे की जाती है?

ビクーニャ: ラマ、アルパカ、ChatGPT とどう違うのですか?

Vicuna: Llama, Alpaca 및 ChatGPT와 어떻게 비교됩니까?

Vicunha: Como se compara a Llama, Alpaca e ChatGPT?

Vicuna: Lama, Alpaka ve ChatGPT ile Nasıl Karşılaştırılır?

Vicuna: Nó so sánh với Llama, Alpaca và ChatGPT như thế nào?

Vicuna：它与 Llama、Alpaca 和 ChatGPT 相比如何？

Letters. Personal Records. Dated Notes.

Astounding Stories of Super-Science July 1931: VOL. VII, No. 1 - The Doom from Planet 4

COMPRA RÁPIDA

comprarapida.co

11-50 employees

Since 2021

COMPANY RANKING

COMPRA RÁPIDA

EVERGREEN INDEX #2863

Representing this company? Click here to claim and customize this page!

Compra Rápida WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

COMPRA RÁPIDA

comprarapida.co

11-50 employees

Since 2021

COMPANY RANKING

COMPRA RÁPIDA

EVERGREEN INDEX #2863

RELATED COMPANIESRANK

STORIES ABOUT COMPRA RÁPIDA

Representing this company? Click here to claim and customize this page!

Compra Rápida WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!