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Polygon, a well-known developer that provides Ethereum scaling solutions, has leaped into the future of Web3. They have introduced an AI chatbot assistant, Polygon Copilot, to their platform.

What is Polygon Copilot?

Imagine a personal guide that can help you navigate the expansive ecosystem of decentralized applications (dApps) on Polygon.

Polygon Copilot is just that! It’s an AI assistant that can answer your questions and provide information about the Polygon platform.

It comes with three different user levels: Beginner, Advanced, and Degen, each designed for users at different stages of familiarity with the ecosystem.

The assistant is built on OpenAI’s GPT-3.5 and GPT-4 models and is incorporated into the user interface of Polygon.

One of the main goals of the Copilot is to offer insights, analytics, and guidance based on the Polygon protocol documentation.

A standout feature of Polygon Copilot is its commitment to transparency. It discloses the sources of the information it gives, which enables users to verify the information and explore the topic further.

Polygon’s step towards integrating AI technology is part of a growing trend in the Web3 world.

Other companies including Alchemy, Solana Labs, and Etherscan are also harnessing the potential of AI.

Using Polygon Copilot

To start with Polygon Copilot, users need to connect a wallet that will serve as the user account.

This account is given credits for asking questions, with new credits added every 24 hours.

And what sets Polygon Copilot apart? It’s not just any plain-speaking AI; it has a flair of its own. Ask it about the top NFT project on Polygon, and you’ll get a response full of personality.

However, it’s essential to remember that like all AI technology, Polygon Copilot isn’t perfect.

Users are cautioned that the AI may provide inaccurate information and to take the chatbot’s answers with a grain of salt.

Polygon has set limits on the number of responses the chatbot can generate to prevent spamming and overload.

What’s Polygon All About?

Polygon presents itself as ‘Ethereum 2.0’, addressing scalability issues within the Ethereum blockchain.

It enhances the value of any applications built on the Ethereum blockchain.

The introduction of the AI assistant is a leap forward for the platform. Whether you are a beginner looking for basic guidance or an advanced user trying to build complex products, Polygon Copilot is there to assist.

It’s also handy for analysts seeking accurate data about NFTs and dApps.

Web3 and the Promise of Data Ownership

Polygon’s use of AI reflects the evolution of the internet, known as Web 3.0. This version of the internet promises safety, transparency, and control over the data created by users.

Web 3.0 operates on blockchain technology, a decentralized system that removes corporate access to private data.

Blockchains were born alongside Bitcoin, the first cryptocurrency, aiming to break free from corporations’ control over our data.

In the spirit of Web 3.0, platforms like Polygon allow users to control access to their data and attach value to it, enhancing data ownership.

As the tech world moves forward, innovations like Polygon Copilot highlight the growing intersection between artificial intelligence and blockchain technology, redefining user experience in the process.

Amazon Web Services (AWS), the cloud computing division of Amazon, has announced a strategic investment of $100 million in a new initiative called the AWS Generative AI Innovation Center.

This move aims to bolster startups and businesses focused on generative artificial intelligence, a rapidly growing field in AI.

The investment underscores AWS’s commitment to staying at the forefront of technological advancements as it competes with industry giants like Microsoft and Google.

Generative AI is a subset of AI that goes beyond traditional classification and prediction algorithms. Instead, it enables the generation of new content, including text, images, and music, based on learned patterns.

This innovative technology has the potential to significantly enhance productivity and creativity by offering novel solutions and ideas.

AWS’s Ongoing Efforts in Generative AI

The AWS Generative AI Innovation Center aims to connect AWS-affiliated experts, including data scientists, strategists, engineers, and solutions architects, with customers and partners to accelerate enterprise innovation in the field of generative AI.

By encouraging collaboration and delivering resources, AWS seeks to empower businesses in leveraging generative AI to drive success and growth.

Sri Elaprolu, heading the AWS Generative AI Innovation Center, highlighted the program’s objectives and its potential impact on various sectors.

Initially, the center will prioritize customers who have demonstrated interest in generative AI, focusing on industries such as financial services, healthcare, life sciences, media and entertainment, automotive, energy, utilities, and telecommunications.

This $100 million investment follows AWS’s recent efforts to promote generative AI, including a 10-week program for generative AI startups and the launch of Bedrock, a platform for building generative AI-powered applications.

Additionally, AWS has been collaborating with Nvidia to develop next-generation infrastructure for training AI models, supplementing its existing Trainium hardware.

The significant economic potential of generative AI is evident, with projections suggesting a potential addition of $4.4 trillion to the global economy annually.

As the AI industry continues to expand, reaching an estimated worth of $15.7 trillion by 2030, AWS’s strategic investment positions them to tap into this immense opportunity.

While challenges remain, such as meeting the demand for AI chips and ensuring enterprise security, AWS remains confident in its ability to deliver customer-centric solutions.

By prioritizing customer needs and leveraging its expertise, AWS aims to solidify its position as a leading generative AI services and support provider.

As the race for dominance in AI intensifies, Amazon’s substantial investment reaffirms its commitment to staying ahead of the curve and driving innovation in the ever-evolving field of generative AI.

Mercedes is set to revolutionize the way drivers and passengers interact with their cars.

The automaker announced plans to integrate ChatGPT, an advanced conversational AI developed by OpenAI, into its infotainment systems.

The integration is part of a beta program launching from June 16, 2023, giving Mercedes customers in the U.S. a chance to experience more engaging and personalized interactions with their vehicles.

A New Era of Interactive Driving

This innovative development allows Mercedes owners to upgrade their existing MBUX (Mercedes-Benz User Experience) systems with ChatGPT’s functionalities.

A simple voice command, “Hey Mercedes, I want to join the beta program,” will allow the users to enjoy this new addition, enhancing their in-car interactions.

ChatGPT is designed to mimic human-like conversation across diverse subjects. While its capabilities include content synthesis, code writing, and even creative tasks like crafting wedding vows, its role in the car environment remains to be explored fully.

Mercedes believes that ChatGPT’s conversational skills will add value to the driving experience.

“Users will experience a voice assistant that not only accepts natural voice commands but can also conduct conversations,” the automaker stated in a press release.

This feature can provide drivers with comprehensive answers to complex questions, assist with destination details, or even suggest new dinner recipes, all while ensuring their focus remains on the road.

While this integration promises to make car journeys more interesting and engaging, some concerns arise.

Are these wide-ranging functionalities necessary for drivers or passengers? What kind of interactions do users actually prefer while on the move? The answers to these questions are yet to unfold.

Mercedes’ choice to partner with ChatGPT, a third-party service, is a strategic decision to elevate its voice interface service.

However, with this enhancement comes the responsibility of managing user data.

Although the conversations between users and the voice interface are stored in the Mercedes-Benz Intelligent Cloud and anonymized, privacy concerns are still relevant.

Mercedes emphasizes that this data collection is crucial for understanding user behavior, shaping the rollout strategy, and improving the voice assistant across markets and languages.

While the feature’s practicality and privacy implications are subjects of ongoing discussion, one thing is clear: this beta program propels Mercedes towards a future where cars are not just machines, but conversational companions.

Time will tell how this new feature impacts the everyday driving experience of Mercedes owners.

Companies across the globe are increasingly recognizing the value of artificial intelligence (AI) and are willing to pay handsome salaries to professionals proficient in AI tools like ChatGPT.

These companies are offering an average salary of Rs 1.5 crore, with some even offering twice that amount.

Since its launch in 2022, ChatGPT, an AI chatbot developed by OpenAI, has revolutionized the tech industry.

Known for its ability to generate human-like text responses, the bot has found applications in a multitude of areas such as essay writing, music composition, and even poetry crafting.

As a result, expertise in this AI tool has become a hot commodity, opening up several job opportunities.

AI Creating Jobs

According to a study by ResumeBuilder, 91% of companies with job vacancies are seeking candidates skilled in ChatGPT, underscoring the belief that AI has the potential to increase productivity, save time, and enhance overall company performance.

A report by Business Insider indicates that companies listed on LinkedIn are ready to offer annual salaries of up to USD 185,000 (approximately Rs 1.5 crore) to individuals proficient in ChatGPT.

HR company Recruiting from Scratch, based in the US, is currently hiring for the position of Senior Machine Learning Engineer, Audio, with job requirements including familiarity with AI tools and platforms like ChatGPT.

The salary for this role ranges from USD 125,000 to USD 185,000 per year.

Interface.ai, a conversational AI tool, is seeking a Remote Machine Engineer with experience in natural language processing and large language models like ChatGPT, offering a salary up to USD 170,000 per year.

Emergence of Prompt Engineering

Despite concerns about AI leading to job displacement, ChatGPT has actually led to the creation of new job roles.

One such emerging profession is Prompt Engineering, which is growing in popularity.

Earlier this year, San Francisco-based AI startup Anthropic posted a job advertisement for a Prompt Engineer and a Librarian, offering a salary of up to USD 335,000 per year (approximately Rs 2.7 crore).

This demand for AI Prompt Engineering roles extends beyond San Francisco, with numerous job openings for prompt engineers found on platforms like LinkedIn and other job search websites.

Online platforms have also begun to offer courses focused on Prompt Engineering to cater to this growing demand.

Google’s DeepMind, the firm behind the historic victory of artificial intelligence (AI) over human intelligence in the complex board game Go, is gearing up for another breakthrough.

Demis Hassabis, the CEO of DeepMind, has revealed that they are developing a more powerful AI language model named Gemini, intended to surpass OpenAI’s ChatGPT in capabilities.

In 2016, DeepMind’s AI program, AlphaGo, astounded the world by defeating a world champion Go player.

Gemini, The Fusion of Advanced Techniques

Hassabis explained that the company is planning to leverage the techniques used in the creation of AlphaGo for the development of Gemini. Gemini, similar to GPT-4, is a large language model that works with text.

“At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models.”

Hassabi

The goal is to merge these technologies to equip Gemini with advanced features like problem-solving and planning.

The foundation of AlphaGo’s prowess was reinforcement learning, a method DeepMind has perfected.

The approach involves software learning to solve intricate tasks that require strategic decision-making through trial and error and performance feedback. AlphaGo also utilized a method called tree search to investigate and remember possible game moves.

The intent is to have Gemini imbibe similar methods and push the boundaries of language models, possibly even performing tasks on the internet and computers.

Hassabis indicated that the development of Gemini is a time-intensive process that might take several months and could involve significant funding.

Gemini’s Anticipated Capabilities

The completion of Gemini could significantly bolster Google’s response to the competition from ChatGPT and other AI technologies.

DeepMind was acquired by Google in 2014 after showcasing impressive results from software that employed reinforcement learning to master simple video games.

It demonstrated how AI can perform tasks once believed to be exclusive to human capabilities, often with superior proficiency.

DeepMind’s reinforcement learning expertise could potentially provide Gemini with unique abilities.

However, the journey towards AI advancements is fraught with risks and uncertainties. The rapid development in language models has raised concerns about misuse of technology and control issues.

Despite these concerns, Hassabis emphasized the extraordinary potential benefits of AI in areas such as healthcare and climate science, making it crucial not to halt its development.

Hassabis and his team, while acknowledging the challenges and potential risks, continue to forge ahead, focused on the development of more powerful and innovative AI models like Gemini.

The future of AI seems promising, yet the path ahead remains one of exploration and learning.

Embattled cryptocurrency exchange FTX has abruptly stopped the sale of its stake in AI firm Anthropic, valued over $500 million, as reported by Bloomberg on Tuesday.

FTX had filed for Chapter 11 bankruptcy protection last November, followed by allegations against co-founder Sam Bankman-Fried for money laundering, fraud, and conspiracy to commit wire fraud.

Court documents filed recently alleged that Bankman-Fried and other high-ranking executives at FTX were involved in commingling over $402 million in customer funds.

The collapsed exchange is reported to owe customers around $8.7 billion, with $6.4 billion in the form of fiat currency and stablecoins.

FTX’s Efforts to Repay Creditors

In January, FTX was given the green light by a federal judge to sell off some assets to repay creditors.

Among the assets FTX has offloaded is derivatives trading platform LedgerX, sold for $50 million – a stark loss compared to the $300 million FTX paid for LedgerX in 2021.

Earlier this month, FTX, with the assistance of financial services firm Perella Weinberg Partners, had shown intentions to offload its shares in Anthropic as part of its clawback strategy to repay creditors.

A clawback in bankruptcy is a legal process where a bankruptcy trustee retrieves property or payments made by the company prior to filing for bankruptcy.

Anthropic’s Success Story

Founded in 2021 by former OpenAI employees, Anthropic has become a front-runner in the current AI boom.

The firm launched Claude AI in March after receiving a $400 million investment from Google earlier this year, supplemented by another $450 million in Series C funding in May, led by Spark Capital.

In May, Anthropic made significant advancements in Claude AI, including the development of a rule-set based on the Universal Declaration of Human Rights, designed to promote ethical behavior and discourage undesirable actions.

A Pause on the Sale

The unexpected halt in the sale of Anthropic shares came after several potential buyers had evaluated private information about the stake.

Anthropic, which is privately-held, is currently valued at $4.6 billion, according to Semafor’s June report.

Buyers in the secondary market for shares in private companies have been eager to acquire stakes in Anthropic, even at a premium, indicating the significant potential of this AI startup.

FTX’s stake in Anthropic, amounting to a $500 million investment made by FTX and Alameda, is among FTX’s most coveted assets.

While the reason for this sudden halt remains undisclosed, it marks another twist in FTX’s ongoing legal and financial turmoil.

By Mukund Kapoor

OpenAI, a leading name in the AI industry, has unveiled its new web crawling bot, GPTBot, to broaden the dataset for training future AI systems, possibly including the next version named “GPT-5,” as indicated by a recent trademark application.

Gathering Public Data

The newly released GPTBot will collect publicly accessible data from websites while steering clear of paywalled, sensitive, and prohibited content.

This web crawler functions similarly to those of search engines like Google and Bing, assuming that accessible information is fair for use.

To block the OpenAI web crawler from accessing a site, the owner must add a “disallow” rule to a file on their server.

OpenAI has assured that GPTBot will scan the scraped data to eliminate any personally identifiable information (PII) or text that contradicts its policies.

However, the opt-out approach is generating ethical concerns around consent. Critics argue that OpenAI’s actions might lead to derivative work without proper citation.

Addressing Past Controversies

The launch follows prior criticism where OpenAI was accused of scraping data without permission for training its Large Language Models (LLMs) like ChatGPT.

In response, OpenAI updated its privacy policies in April.

The new web crawler represents OpenAI’s need for more current data to maintain and enhance its LLMs.

The move may indicate a shift from OpenAI’s initial focus on transparency and safety, understandable as ChatGPT remains the most used LLM globally.

OpenAI’s products heavily rely on the quality of data used for training, and the GPTBot aims to gather that essential data.

Competition in the AI Space

Meta, the social media titan, has also been working on AI, offering its model for free unless used by competitors or large businesses.

While OpenAI’s strategy revolves around using crawled data for profitable AI tool ecosystems, Meta aims to build a profitable business around its data.

OpenAI’s ChatGPT currently boasts over 1.5 billion monthly active users, and Microsoft’s $10 billion investment in OpenAI is paying off, as ChatGPT integration has enhanced Bing’s capabilities.

As OpenAI’s GPTBot represents an advancement in AI capabilities, it also reopens copyright, consent, and ethics debates.

As AI systems become more advanced, striking the right balance between transparency, ethics, and technological capability will continue to challenge industry leaders.

The new web crawler’s launch highlights the complexities of innovation in the AI space, where benefits in efficiency and ability may come with potential ethical trade-offs.