Advanced AI Solutionsis in the Drones Industry

Advanced AI Solutions

Today I am speaking with Ilan Rakhmanov, the Founder & CEO of ChainGPT and we'll discuss the innovative integration of artificial intelligence within the Web3 and blockchain landscapes, highlighting the current state, challenges, and future opportunities of this fusion. We will also discuss the critical skillsets needed for professionals in this evolving field, the genesis and mission of his company in bridging AI with blockchain, and the potential of AI-driven tools to transform digital art, news aggregation, and blockchain analytics. Please introduce yourself and tell us what you do? Hi, my name is Ilan Rakhmanov, I am the CEO & Founder of ChainGPT, the AI-powered Web3 infrastructure providing a diverse suite of tools and services. I am a serial entrepreneur and businessman, and for the past couple of years since founding ChainGPT, I have been working to bring the company and its AI services to Web3 and blockchain to help fill the void of real AI and Web3 integration. My experience leading multiple 7-9 figure companies has included roles across various industries and sectors ranging from software and IT to business, law, design, and marketing. I’m never bored. Leading the ChainGPT team, we have collaborated with more than 70 Web3 companies and industry frontrunners. Can you describe the current state of integration between AI and blockchain technologies in the Web3 space? As of now, integration is still quite nascent, but we are seeing an influx of innovative applications. We’re witnessing continuous R&D being done behind the scenes, so we can certainly anticipate more use cases and integrations in the pipeline. What skillsets are becoming increasingly important for professionals working at the intersection of AI, blockchain, and Web3? As with any new industry, the skillsets we see quickly becoming a prerequisite for professionals working at the intersection of AI, blockchain, and Web3 are an increased proficiency in existing industry skills converging with new knowledge and technical prowess tailored to this fresh industry. Existing skills such as coding language, large dataset analysis, and machine learning, normally reserved for computer developers and IT departments are quickly becoming a general skill required across the board. Similarly, soft problem-solving skills, teamwork, and effective communication have evolved to become similarly critical. However, these base-level requirements must also embody novel or more advanced capabilities unique to this new industry. These capabilities include skills and knowledge surrounding smart contract creation, development and auditing, advanced natural language processing (NLP), reinforcement learning models, consensus mechanisms, advanced cryptography, and zero-knowledge proofs (ZK-proofs), alongside familiarity with blockchain development platforms such as Ethereum, Solana, and Polygon. This might sound incredibly specific now, but all of this knowledge and skillsets will inevitably take the place of the previous “Microsoft Office proficiency” requirement of the early 2000s. A compilation of many, if not the vast majority, of these skills will become standard requirements for any professional operating in the intersection of AI, blockchain, and Web3. Can you describe the genesis of ChainGPT and its mission within the Web3 and blockchain space? We established ChainGPT in 2022 as we recognized the continuously growing role of AI across every sector, and the gaping infrastructure void to facilitate and support this. ChainGPT is an AI infrastructure platform focusing on the Web3 blockchain and crypto space. Our mission is to provide individuals and startups with a comprehensive suite of AI solutions tailored specifically to the evolving needs of this industry. Since launching, we’re thankful to be backed by industry leaders such as Google, to be a part of the prestigious NVIDIA Inception Program for Startups, and to have forged partnerships with more than 70 leading Web3 companies, including BNB Chain and Tron. That being said, ChainGPT is not just about AI—it's about community engagement and empowerment, and we embody that being ensuring that our staking and governance models allow $CGPT holders to shape the ecosystem's future. Ultimately, ChainGPT's genesis and mission revolve around providing accessible and advanced AI solutions to fuel innovation and success in the Web3 and blockchain spaces, supported by a strong community and strategic alliances. Could you elaborate on the technology behind ChainGPT’s AI News Auto-Model and how it ensures the relevance and accuracy of the curated content? Our fully automated AI Generated News service aggregates breaking news from only the most trusted sources within crypto and Web3, and then extracts valuable insights from these publications. Given the unique nature of how crypto and blockchain news is disseminated, that does include reliable or verified social media accounts. After aggregating, the tool generates short, to-the-point summaries that are easy for readers to consume on the go. Aside from that, the service employs real-time learning capable of catering to diverse use cases, stories, interactive trading guides, and more. How does the AI NFT Generator align with current digital art and blockchain technology trends? Even before the explosive launch of ChatGPT in November 2022, we had already begun to see growing use of AI-art generators like Dall-E and Midjourney—despite not being as advanced as the tools we have now. The NFT market itself has always been largely composed of unique digital art, so our use of generative AI to mint unique art collections and allow users to mint their own NFTs is just the natural evolution of the NFT space. In your view, what are the most promising opportunities that arise from the convergence of AI and blockchain in the Web3 era? At face value, they are quite different technologies with different strengths, but there are countless ways for them to co-exist. The clearest intersection between AI and blockchain can be seen in AI-arbitrage bots, AI tools creating a better user experience, and NFT generation. However, there are more expansive, infrastructure-level possibilities or applications that cover areas like boosting data ownership and transparency. Aside from that, generative AI’s approachability and fluency can help guide new Web3 users through a fairly complex interface, helping them avoid mistakes and possible scams. But this is definitely an area where we will continue to see a steady stream of innovation and interesting applications. Can you discuss the capabilities of the ChainGPT Chatbot, especially in addressing technical blockchain and crypto queries? The ChainGPT Chatbot allows users to access information and answers to any question related to or within blockchain and crypto. Not unlike the news service, the chatbot utilizes the most trustworthy sources within crypto and blockchain to gather, analyze, process, and distill information while extracting valuable and relevant insights. By doing so, our chatbot provides a fast source of information to any query no matter how general or technical it may be in a way understandable to the user who might not have as much experience with blockchain or crypto jargon. What are the most significant challenges and opportunities in AI-driven blockchain analytics? Given the immense reliance on data to power large language models in generative AI, the biggest challenge will be trying to ensure the integrity of the data being used to train these analytics tools. In Web3 especially, where there can sometimes be a financial stake, it is critical to ensure that those designing these models don’t use them to serve their financial interests. With most of your team being developers, how does ChainGPT foster a culture of innovation and collaboration? First of all, one of my most important responsibilities as CEO is ensuring that our developers, product teams, and everyone across the company understand the value in collaborating. It’s on me to foster that as a startup leader overseeing a team that works across borders. Thankfully we have an incredible group of people who are creative, thoughtful, and bring a lot of different perspectives and experiences to the table. How does ChainGPT plan to grow and engage its user community further? We just need to keep doing what we are doing—building meaningful products and tools that regular users and developers can use. We are invested deeply in our IDO launchpad and incubator which helps solidify our ecosystem and we are deeply connected with our community across multiple social media platforms. By continuing to build and engage, we will see our community grow. Where do you see ChainGPT in the next five years, especially in the rapidly evolving Web3 environment? I fully anticipate Web3 becoming the current internet iteration in five years. With that said, we see ourselves as an integral component of a robust Web3 ecosystem by continuing to provide unique and innovative AI solutions that either tackle space challenges or enhance other aspects. There’s no question the industry will look different in five years. Still, as early innovators of AI in blockchain, we will remain at the forefront of all industry developments, finding a niche or mainstream issue to improve or solve. What future trends do you anticipate in integrating AI and blockchain technologies, and how might these shape the Web3 landscape? I anticipate many future trends, but chief among them will be the use of blockchain to make AI more transparent and secure. This concept is still very academic but many of the brightest minds are working on applying it in numerous ways. For instance, imagine using blockchain to give individuals complete control over their personal data. With AI models becoming increasingly powerful as we compile more data, enabling Web3 to govern these models transparently can enable them to scale in a way that benefits the entire population. Of course, we’ll need to wait and see where regulations also come into play in this realm. On a micro level, I fully anticipate AI being used to help developers build, scale, and deploy apps rapidly. I also fully expect to see AI being used to track market shifts and trends more accurately and transparently.

Exploring AI's Impact on Blockchain with Ilan Rakhmanov

, co-founder of began his journey as a University of Nevada, Las Vegas (UNLV) student and is now an influential figure in the global tech community. He embodies the essence of innovation and ambition so many founders aspires to. Tomasik most attended the AMD Advancing AI Event, where TensorWave announced a significant partnership. Piotr Tomasik TensorWave Inc. A UNLV College of Engineering alumnus, Piotr's journey is not just about personal success; it's a testament to the potential of Las Vegas's tech sector. His role in co-founding TensorWave Inc. and steering it towards groundbreaking collaborations is a beacon of inspiration for upcoming tech enthusiasts in the city. Under Piotr’s guidance, TensorWave has not only made strides in AI technology but also cemented Las Vegas's position on the global tech map. The recent partnership with AMD and GigaIO, leading to the development of the TensorNODE infrastructure powered by AMD Instinct MI300X accelerators, is a milestone in AI technology. This collaboration isn't just a technological triumph; it's a narrative of how local talent can propel a city into the limelight of the global tech arena. A Testament to Local Talent: Piotr Tomasik’s Impact on Las Vegas Las Vegas Chief Information Officer Michael Lee Sherwood's commendation of Piotr Tomasik underscores the significant impact he has had on the city’s technology landscape. Sherwood’s praise highlights how Tomasik's innovative approach and commitment to excellence have not only accelerated the growth of the local tech sector but also enhanced Las Vegas's reputation as a hub for advanced AI solutions. “In my eight years as the CIO for the City of Las Vegas, I've had the privilege of witnessing firsthand the remarkable impact Piotr Tomasik has had on our technology landscape. Piotr's innovative approach and commitment to excellence have not only accelerated the growth of our local tech sector but have also placed Las Vegas on the map as a hub for advanced AI solutions. Celebrating our local tech leaders is a cornerstone of our city's evolution into a leading smart city, driven by cutting-edge technology and ambitious talent.” Beyond his achievements with TensorWave and the groundbreaking TensorNODE infrastructure, Piotr Tomasik's career spans various critical roles in the tech ecosystem. As a celebrated Las Vegas Top Tech Exec, a Vegas INC 40 under 40 awardee, and a proud UNLV Alumni of the Year, Piotr's contributions extend well beyond individual companies. His co-founding of StartUp Vegas and active role as a General Partner at Vegas Tech Ventures signify his dedication to cultivating a thriving tech community. Piotr's involvement as an advisor to numerous tech-focused organizations further underscores his commitment to guiding and nurturing the next generation of tech innovators. This multifaceted experience makes Piotr a beacon for aspiring entrepreneurs and investors alike, proving his expertise is not just in technological innovation but also in fostering a vibrant startup ecosystem. The Future of AI and Las Vegas: Piotr's Vision Piotr’s vision extends beyond technological advancements; it's about elevating Las Vegas in the global tech community. His excitement about bringing TensorWave's innovative solutions to the global market, in collaboration with industry giants like GigaIO and AMD, reflects his dedication to both his hometown and the broader field of AI.

POWER LEADER: TensorWave co-founder Piotr Tomasik secures key partnership at AMD Advancing AI event 

The business impact companies are making with is driving investment in digital transformation across the board. Faced with multiple waves of disruption in a COVID-19 world, almost 92% of companies are reporting plans to spend the same or more on data/AI projects, according to a recent survey from . Small wonder. Data mature companies business-critical benefits from using big data, including: big data analytics NewVantage Partners are citing Informed decision-making Cost reduction Better understanding of customers New product development Data monetization Offensive drivers such as new competitive advantages, innovation, and transformation override defensive ones as change is becoming the only market constant nowadays. Let’s explore what business benefits exactly companies are achieving with to edge out the competition. big data But a few words about big data first Big data came into prominence a decade ago, with an explosive growth in data generated every second in the new world of digital everything. A quick fact: we created roughly 2.5 quintillion data bytes daily in 2020, with almost 90% of all current data generated in the last couple of years. Combining structured, semi-structured, and unstructured data (imaging, text, videos, social media posts, sensor data, etc.), big data is not just big but complex for traditional analytics systems. This is perhaps a reason that has never been analyzed for insights or larger trends (another quick fact). and new techniques, however, have made it possible to unearth hidden patterns and correlations in the massive volumes of data companies have been collecting for years. And big data has started talking, and making big business impacts too. 60% to 70% of all data within organizations Advanced AI solutions So, what is the impact of big data on business today? As all kinds of companies are trying to ride the big data wave for various business benefits, big data adoption doesn’t come easy. This is because just like anything else with big data, are big as well, from poor data quality to silos, lack of coordination, and business misalignment. There are a few success stories, though. Dive in. challenges Retail & Ecommerce With heightened customer expectations, the rise in online shopping and returns, and Amazon being a major competitor almost to everyone, increasingly more retailers are relying on big data analytics to capture a business impact. bring leading companies a lot of business benefits, including the ability to win customers with personal recommendations, forecast demand and revenue, improve day-to-day operations, and prevent fraud. Big data/AI technologies in retail Take Walmart, a leading retailer in the world that’s been on a transformational journey for a few years. Putting data democratization at its heart, Walmart has set up an analytics hub to provide employees with controlled access to data from hundreds of sources. Data-driven teams can now find quick solutions, like it was with for a particular item. Data manipulation helped them discover that the product price was uncompetitive due to simple miscalculations, and take prompt action. a grocery team puzzled by a drop in sales Major retail stores use video and data mining techniques to understand customer behavior patterns. This provides them with insights into questions about dead spots in the store ignored by customers, optimum staffing, say, on a Friday night, products that are in demand in the hot weather, and many, many others. Using market basket analysis to explore customers’ demographics and purchasing patterns, retailers are making their products look like a total steal with adjusted prices and layouts. analytics enabled by CCTV Ecommerce sites, on the other hand, can better target users with product recommendations by tracking clickstream data and other customer activity. The data gives them insights into channels driving the most traffic, pages or products attracting the most visits, who their most profitable customers are, and where the site might be losing users. By applying text mining to queries, they also help customers find the desired product much faster. Big data analytics empowers inventory management with end-to-end visibility. A 360-degree view of stock helps prevent missed opportunities that stem from product unavailability, non-synchronized stock levels across sales channels leading to overselling, or slow delivery. Amazon, for instance, has presented a patent for its ’ ‘ system that can predict what people want to buy before they even place their orders. anticipatory shipping Finding new customers has also been made easy with sophisticated big data/AI technologies when implemented in CRM systems. These platforms not only track unstructured email and calendar data but automate follow-up sequences and flag warm leads. Marketing “The aim of marketing is to know and understand the customer so well the product or service fits him and sells itself,” — Peter Drucker, a celebrated management consultant and educator. Marketing and sales teams are leading the way in big data analytics, making a great business impact with big data. The three types of data they are gathering — customer, financial, and operational data — enable a more accurate analysis of target audiences, financial performance, and business processes. Netflix is a great example of how data-powered advertising can fuel subscriber growth despite counterintuitive decisions like a VPN ban and a price hike in 2016. Those who are in the fan club know how they send you recommendations of the next show to watch. Netflix’s recommendation engines and new content production decisions rely on what titles people search or watch, time spent selecting movies, how often playback is stopped, ratings given, etc. Hollywood screenwriting star William Goldman said, “Nobody, nobody – not now, not ever – knows the least goddamn thing about what is or isn’t going to work at the box office.” Well, Netflix knows! Google and Facebook also know a few things about data-driven advertising, deriving huge business benefits from big data. By collecting and analyzing massive volumes of personal data we share, they serve better targeted and more personalized ads of products and services that we might be actually interested in buying. With the proliferation of smartphones, big data analytics has enabled hyper-localized advertising (which, let’s admit, is quite creepy). Capturing location and demographics data, analytics platforms can send shoppers near the store an ad offering discounts or other initiatives. Another good example of big data and its business impacts in marketing is the coupon story of Kroger. The US largest grocery network mails highly personalized coupons to shoppers, reporting within the next six weeks. Studying each customer’s DNA rather than segmenting them demographically, Kroger offers coupons for what people actually like, meaning that a Coke drinker is unlikely to be embarrassed with a Pepsi coupon offer ever. redemption rates at more than 70% Healthcare by storm, helping predict epidemics, cut down treatment costs, avoid preventable conditions, and improve the overall quality of our lives. Operational improvements are also on the list of sought-after big data business benefits. Insights are flowing in from multiple sources that include clinical data, electronic patient records, payer records, patient portals, results of medical examinations, wearables, smartphones, genetic databases, and other. Big data analytics is taking healthcare Electronic health records (EHR), perhaps the widest application of big data in healthcare, give health professionals access to complete information on a patient, including demographics, medical diagnoses, prescriptions, allergies, etc. EHR systems improve care through automation and better collaboration between providers, sending screening or vaccination reminders or alerts of contraindicating conditions, abnormal lab results, or drug interactions. They empower , with examples here featuring an ML-driven predictive analytics tool built by to accelerate antibiotic treatment and reduce sepsis mortality using EHR data. predictive analytics in healthcare North Oaks Health System Big data business benefits in healthcare include optimized staffing levels. A group of French hospitals, for instance, are using an . The platform can predict emergency department visits and admissions for the next 15 days, powered by a database on more than 470,000 patient encounters and additional data on external factors such as weather, holidays, and flu incidence that correlate with hospital visits. analytics platform to address the overcrowding problem Another important area where big data is making a great impact in healthcare is epidemic management. During the 2014-16 Ebola virus outbreak in West Africa, researchers turned to data on the location and frequency of calls to helplines to map the population’s movements in the region. A similar mobile phone data analysis was used after the Haiti earthquake in 2010 for targeting relief operations and predicting the spread of the subsequent cholera outbreak. Big data research is making big strides in improving the detection and treatment of certain conditions. Examples include technology company that has created a massive library of clinical and molecular data to enrich context on each patient’s cancer case for more personalized treatment options. In the dermatology field, modern AI algorithms trained to detect benign and malignant skin lesions of board-certified clinicians. The automatic classification of skin lesions based on images is deployable on smartphones, holding the potential to increase low-cost access to vital diagnostic care. Tempus have achieved the accuracy Finance The increasing use of data is that will be shaping the banking sector in the next decade. For banks and other financial institutions, the impact of big data on business centers around new levels of security and better customer loyalty driven by personalized offerings. named among the major trends Better customer service empowered by big data analytics is on the list of top priorities for the Royal Bank of Scotland (RBS). The RBS analyzes packaged bank accounts to detect whether a customer might be paying twice for the same service and uses analytics to spot customers who could save money from consolidating their loans. Their systems also send deal renewal reminders to mortgage holders when they approach an automatic transfer to a more expensive variable rate. Fraud prevention is another common application of big data in the banking sector. Lloyds Banking Group, for instance, creates what it describes as audio fingerprints of customer calls by analyzing unique call features (location, background noise, calling history, etc.). Meanwhile, American Express a 100% improvement in its resolution rate for digital fraud and a 21% reduction in POS disruption since adopting AI-powered data analytics in 2014. AmEx also uses big data for new customer acquisition via online channels and the development of apps linking cardholders with merchants on personalized offers. is reporting Big data delivers big impacts when it comes to risk management in banking. Success stories include Singapore-based that has reduced the time cycle of calculating the value at risk (the risk of loss for investments) from hours to minutes and that has achieved greater accuracy in financial risk prediction with the help of automated pattern recognition. United Overseas Bank (UOB) Morgan Stanley Education Big data/AI technologies are , making it possible to analyze the student’s performance and behavior in real time, improve teaching approaches, and reinvigorate entire education systems. revolutionizing education By capturing data such as test scores, response times to questions, or questions that students fail or answer successfully, big data analytics systems allow educators to personalize the learning process and improve students’ results. With real-time assessment tools and sophisticated applications, Ashford School in the UK, for instance, has not only created a more optimal learning environment but . reduced overall IT costs Big data technologies are also used to monitor students’ facial expressions and other biometric data via cameras or wearables to gauge their learning engagement or boost safety ( behind this big data application is delicate though). the ethics Assisting students with a career choice is another important application of big data in education. College planning platforms like help students understand fields they are interested in, track progress toward their educational goals, and follow schools of their liking. Overgrad Ending note Many companies across industries have woken up to big data technologies and business impacts they are delivering. The game is on, and more is coming. According to , the big data analytics market should reach $103 billion by 2023. Meanwhile, global spending on big data, , is projected to grow at a CAGR of 13.2% between 2020 and 2022. This means competition will get bigger. Don’t hesitate, go big too. Wikibon reported at $180 billion in 2019 If you don’t know how to get started with a big data journey in your industry or are stuck in the middle, big data experts. They will be happy to share their experience and expertise. contact ITRex

The Big Impact of Big Data on Businesses Today

Imagine you are at the polling booth; dozens of political parties' banners are printed across it. Most of them you've never seen before. However, you know that the button you press determines the government for the coming years. How are you going to choose? Before we discuss how - let's begin by figuring out the why. Why do people face this challenge? Privileged people think it is okay to be apolitical. The reason people are apolitical is it requires rational investment to make an informed choice on the polling booth- reading the local newspapers, comparing the merits of candidates, watching the candidates' speeches. But, unfortunately, most people find all this boring or not worth their time. But people forget we are living in an AI-driven world. AI technologies work on numerous tools that help us make smart decisions for complex subjects. From flight tickets, life insurance, and mobile plans to personalized suggestions like books to read, artists to listen to, and movies to watch, AI helps us make the suitable decision quickly. So, could AI help us select the right political leader? Let's find out. FiscalNote FiscalNote's complete software solutions connect the world to government policies. They promote themselves as a "non-partial, authentic source platform." Their core motive is to provide policy insights to organizations for optimal decision-making. How this can be useful for elections: Voters can use this AI service to educate themselves about the policies that will impact their lives and families. Also, the AI sends significant alerts, informing users about the policies of political parties prior to the elections, which help voters make a better choice on the election day. iSideWith It's another AI technology company that lets people compare political parties, candidates through engaging quizzes, discussions, and much more. How this can be useful for elections: Due to the overwhelming information available on the web, it has become quite difficult for voters to identify the trusted sources. In that case, the platforms conduct political surveys daily to help find credible sources and keep the users informed about the ongoing political issues. Expert.ai Expert.ai leverages the AI technique known as "sentiment analysis" to recognize human behavior on social media platforms. For example, this AI program helps political parties to know where they need to concentrate more to increase their chance of winning. How this can be useful for elections: Specifically, this AI can help predict voter turnout. Therefore, the election officials will prepare and conduct the polls more securely, accurately. Advanced Symbolics Inc. The company's AI technology is named Polly, which assesses people's online behavior, policy trends, politicians' popularity, and other significant information that impact businesses' success. However, one could easily witness how this AI evaluates social media campaigns to forecast real-world actions. How this can be useful for elections: It will help see what motivates people to vote to develop campaigns to increase the number of voters. Final Thoughts In unprecedented times like 2021, when everything in the country is at a standstill, why are we conducting elections, standing in long queues for hours to cast our vote? We need technologies that enable virtual voting. We need multi-step verifications, voter ID scanners, reliable government portals for a free and fair electoral process. Although, it is a long road ahead. But If we integrate the above-mentioned advanced AI solutions into the elections, we can witness optimal changes in the future. As a society, the more of us become politically aware of the issues, the more beneficial the result of elections will be.

Selecting Better Leaders: Using AI Technology At The Polling Booths and Beyond

The emergence of technology is playing an inevitable role in business. It’s drastically transforming the way people work together in an organization. Both these technologies are revolutionizing every aspect of our life.  These technologies are creating a culture where the collaboration of IT leaders and businesses results in realizing values from all generated data. Artificial Intelligence and Big Data work hand in hand following the futuristic approach. In this progressive era, these technologies are a major part of our digital future ensuring rapid growth. These technologies are introducing a variety of tech innovations and exploring ways to overcome industry challenges by changing the landscape of how industries work. According to Satista, AI will grow into a $118.6 billion industry by 2025. The global big data and business analytics market was valued at 168.8 billion U.S. dollars in 2018 and is forecast to , with a five-year compound annual growth rate (CAGR) of 13.2 percent. grow to 274.3 billion U.S. dollars by 2022 Power of Big Data & Artificial Intelligence These growing technologies hold the potential of constant growth. Its contribution is expanding with its growing requirement in the business. Every organization holds a vast amount of data available of all types. To maintain this vast amount of data one must invest in these technologies. Big Data Big data provides with an outstanding way to increase business revenue. It analyses data and extracts important information from data sets. Using traditional data processing application software to manage data sets can be a bit complicated. Therefore, big data is used in multiple industries and largely focuses on financial analysis Clinical analysis, fraud analysis, Supply chain analysis, and HR analysis. According to IBM, Over 80% of data is dark data, and it is expected to rise 93 % by the year 2020. What is Big Data? Big data is something beyond its characterstics. It’s one of the modern-day technology which helps you manage any data structured or unstructured. Big data is transforming an extensive variety arriving in increasing the volume and ever-growing velocity. It's three associated characterstics are; Volume - Helps you know the current amount of data Variety - Structured and unstructured data Velocity - The speed at which data is produced and processed It allows you to take a strategic decision and improves the overall decision-making process whether it's managing finance and planning business strategies. How Big Data Help Industries? Align Data Considering Business Goals Improved Management Boost Sales Maximize Customer Value Promoting Personalization Effective Advertising Predict Buyers Behavior Email Campaigns  Segment Increases Customer Responsiveness Artificial Intelligence Artificial intelligence is designed to process human intelligence by machines. It helps the businesses to grow and operate with industries seamlessly. For effecient data analysis and data scanning, analytics using artificial intelligence software and providing with advanced solutions. AI helps organizational leaders discover patterns by user consumption, history records, and uses the data for providing customers with lucrative offers. It offers creative, more responsive, straightforward, and efficient assistance by analyzing clients behaviour. Artificial Intelligence Definition Artificial Intelligence (AI) assists businesses to find an enormous way to enhance their business. It encourages organizations to analyze steadily changing user conduct, reduce inaccuracy, and deliver exquisite user experiences. Establish your brand in the market using AI-based solutions and gain a higher profit at minimum investment. Modern implementation of Artificial Intelligence helps top-notch companies to grow and do their job better. It offers a personalized experience for consumers while identifying the potential buyer and re-target the existing buyers. How Artificial Intelligence Help Industries? Solve Problem Across the board Increase sales Detect fraud Improve customer experience Predictive analysis Real-time assistance Business insight from a cloud database Help to make a smarter decision Fraud detection Streamline process Artificial Intelligence & Big Data: Driving-force of Future Growth Artificial Intelligence is the wider umbrella of Machine Learning used with Big data for the rapid expansion of businesses. AI and big data are contributing to various business verticals while managing data with the utmost ease.	 It is enlarging its boundary in technology and knowledge with machine learning. Its been in action for decades, managing an enormous amount of data available of all types. It’s estimated that by 2020, every person on earth will generate 1.7 MB of data every second, . according to DOMO AI can help you analyse Big Data to detect irregularities in the data sets. Artificial intelligence can help you identify a potential problem that needs attentation in big data sets seamlessly. Big data under the influence of AI can help you determine the condition that has the probability to impact the future outcome. AI can detect anomalies while analysing Big data using Bayes Theorem. AI can help industries beat human supervision while recognizing Bid data patterns that might remain undetected. Artificial intelligence can analyze Big data to look or patterns in bars and graphs underlying data sets. AI analytics applied to Big data offers a strong value proposition with the rapid growth of the internet of things. Big data with AI contributing to widening the gap that exists between workers, nations, and businesses. Reap economic benefit adopting AI & Big data while attracting the right talent and get the great opportunity to grow. Give birth to innovation using these advance technologies AI & Big data and transform the way you work for better user experience. With the explosion of technology advancement, these technologies are growing at an astonishing rate. These technologies provide business with the ability to access and act on data bringing effective results. Data helps you introduce innovation while offering outstanding transformation that can result in accelerating your business at a rapid rate. Data holds the power to specialize in any field. It helps you utilize the data in the most effective way and offers an exceptional way to increase business revenue by analyzing data and extracting information from data sets. Artificial intelligence and Big data allow the business to consider and analyze data to improve the entire business process. These technologies are trending and providing with accurate results while forecasting and predicting buyers behaviour for better results. Adopt these modern technologies and expect visible growth in the business. (Image Credit Source: VectorStock)

How Big Data and Artificial Intelligence Will Go Hand in Hand?

In the rapidly evolving world of data storage and processing, combining efficient cloud storage solutions with advanced AI capabilities presents a transformative approach to handling vast volumes of data. This article demonstrates a practical implementation using MinIO, Langchain and OpenAI’s GPT-3.5 model, focusing on summarizing documents stored in MinIO buckets. The Power of MinIO MinIO is open-source, high-performance object storage that is fully compatible with the Amazon S3 API. Known for its scalability, MinIO is ideal for storing unstructured data such as photos, videos, log files, backups and container images. It’s not just about storage; MinIO also offers features like data replication, lifecycle management and high availability, making it a top choice for modern cloud-native applications. Integrating Langchain and OpenAI , a Python-based tool, facilitates the interaction between document loaders and AI models. In our use case, we combine Langchain with OpenAI’s model to summarize documents from MinIO buckets. This setup exemplifies how AI can extract essential information from extensive data, simplifying data analysis and interpretation. For additional information and supporting materials related to this article such as notebooks and loaded documents, please visit the in the directory. Langchain gpt-3.5-turbo-1106 MinIO Github repository langchain-s3-minio Installing Langchain Before diving into the implementation, ensure you have Langchain installed. Install it via pip: pip install --upgrade langchain This will encapsulate all the required libraries we will be using for our S3 loaders and OpenAI model. Step 1: Langchain S3 Directory and File Loaders Initially, we focus on loading documents using Langchain's and . These loaders are responsible for fetching multiple and single documents from specified directories and files in MinIO buckets. S3DirectoryLoader S3FileLoader MinIO Configurations and Langchain S3 File Loader from langchain_community.document_loaders.s3_file import S3FileLoader

# MinIO Configuration for the public testing server
endpoint = 'play.min.io:9000'
access_key = 'minioadmin'
secret_key = 'minioadmin'
use_ssl = True

# Initialize and load a single document
file_loader = S3FileLoader(
    bucket='web-documentation',
    key='MinIO_Quickstart.md',
    endpoint_url=f'http{"s" if use_ssl else ""}://{endpoint}',
    aws_access_key_id=access_key,
    aws_secret_access_key=secret_key,
    use_ssl=use_ssl
)

document = file_loader.load() Python Langchain Example - S3 File Loader Langchain S3 Directory Loader: from langchain_community.document_loaders.s3_directory import S3DirectoryLoader

# Initialize and load documents
directory_loader = S3DirectoryLoader(
    bucket='web-documentation',
    prefix='',
    endpoint_url=f'http{"s" if use_ssl else ""}://{endpoint}',
    aws_access_key_id=access_key, 
    aws_secret_access_key=secret_key, 
    use_ssl=use_ssl
)

documents = directory_loader.load() Python Langchain Example - S3 Directory Loader Summarizing with OpenAI Step 2: After loading the documents, we use OpenAI's GPT-3.5 model (which are included in the Langchain library via ) to generate summaries. This step illustrates the model's capability to understand and condense the content, providing quick insights from large documents. ChatOpenAI To access the OpenAI API, you can acquire an API key by visiting the . Once you have the key, integrate it into the code below, to harness the power of GPT-3.5 for document summarization. OpenAI platform Code Example for Document Summarization: from langchain_openai import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnableLambda
import os

# Set your OpenAI API key
os.environ['OPENAI_API_KEY'] = 'your-openai-api-key'
model = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-1106")

prompt = ChatPromptTemplate.from_template(
    "Summarize the following document '{document_name}':{context}Please provide the summary and key points."
)

loaded_documents = [documents, document]  # From S3 Loaders
flattened_documents = [doc for sublist in loaded_documents for doc in sublist] 

for loaded_document in flattened_documents:
    document_text = loaded_document.page_content
    document_name = getattr(loaded_document, 'name', 'Unknown Document')  # Assuming each document has a 'name' attribute
    chain = (
        RunnableLambda(lambda x: {"context": document_text, "document_name": document_name})
        | prompt
        | model
        | StrOutputParser()
    )
    summary = chain.invoke(None)
    print("Summary:", summary) Python Langchain Example - Summarizing Documents with OpenAI API Below is the output from running this demo, and is a result of integrating LangChain with OpenAI’s GPT-3.5 and MinIO S3 storage; the output has been shortened for demonstrative purposes: Summary: The document is a quickstart guide for MinIO, a high-performance object storage system that is compatible with Amazon S3. It explains how to run MinIO on bare metal hardware or in containers. For Kubernetes environments, it recommends using the MinIO Kubernetes Operator. The key points are:

- MinIO is a high-performance object storage system.
- It is released under the GNU Affero General Public License v3.0.
- MinIO is API compatible with Amazon S3.
- It can be used to build high-performance infrastructure for machine learning, analytics, and application data workloads.
- The guide provides quickstart instructions for running MinIO on bare metal hardware or in containers.
- For Kubernetes environments, the MinIO Kubernetes Operator is recommended. Response from OpenAI API This method highlights an interesting way to load documents from S3 storage into an LLM using the Langchain framework to process them, while OpenAI’s GPT-3.5 model generates a concise summary and key points of the which is fetched from the server. The use of AI to analyze and condense extensive documentation, provides users with a quick and thorough understanding of essential aspects like installation, server configuration, SDKs and other MinIO features. It showcases the capability of AI in extracting and presenting critical information from comprehensive data sources. MinIO_Quickstart.md play.min.io Loading Documents from MinIO Buckets with Langchain The integration of MinIO, Langchain and OpenAI offers a compelling toolset for managing large data volumes. While Langchain's S3 loaders, S3DirectoryLoader and S3FileLoader, play an important role in retrieving documents from MinIO buckets, they are solely for loading data into Langchain. These loaders do not perform actions related to uploading data into buckets. For tasks like uploading, modifying or managing bucket policies, the is the appropriate tool. This SDK provides a comprehensive set of functionalities for interacting with MinIO storage, including file uploads, bucket management and more. For additional information, please see , . MinIO Python SDK Quickstart Guide — MinIO Object Storage for Linux Python Client API Reference — MinIO Object Storage for Linux While Langchain streamlines the process of fetching and processing data using AI models, the heavy lifting of data management within the MinIO buckets is dependent on the MinIO Python SDK. This is an important distinction that must be understood by developers and data engineers building efficient, AI-integrated storage solutions. For a thorough understanding of MinIO's capabilities and how to utilize its Python SDK for various storage operations, refer to MinIO's official . documentation By using MinIO object storage as the primary data repository for AI and ML processes, you can simplify your data management pipeline. MinIO excels as a one-stop solution for , which is crucial for effective AI and ML operations. This streamlined approach reduces complexity and overhead, potentially accelerating insights by ensuring swift access to data. storing, managing, and retrieving large datasets For those interested in delving deeper into the integration of MinIO with Langchain to enhance LLM tool-use, the article “ ” offers a comprehensive exploration of the subject. Developing Langchain Agents with MinIO SDK for LLM Tool-Use Good luck in your development endeavors! We hope continues to play a key role in your AI/ML journey. Reach out to us on and share your insights and discoveries! MinIO Slack

Managing Large Data Volumes With MinIO, Langchain and OpenAI

The Importance of Security Vendors in Ensuring Web3 Safety As we move towards a more decentralized web, it's becoming increasingly clear that blockchain technology's advancements present new and complex security challenges. It's to ensure the widespread acceptance of web3. This way, we can create a digital landscape that's . With the right approach and a commitment to innovation, we can build a decentralized web that's both safe and effective, opening up new possibilities for the future of the internet. crucial to prioritize trust and security secure and reliable and can be trusted by individuals and businesses alike Security Challenges in the Decentralized Web Vulnerabilities to Smart Contract Exploits, DDoS Attacks, and Data Breaches Decentralized applications operate on without centralized control, making them vulnerable to Smart Contract exploits, distributed denial of service (DDoS) attacks, and data breaches. These vulnerabilities can lead to substantial financial losses for individuals and businesses alike. Additionally, decentralized systems are often more complex than centralized ones, requiring more effort to secure them fully. open, permissionless networks Common Code Vulnerabilities and the Need for Ongoing Maintenance Moreover, the open-source nature of Web3 means that code vulnerabilities are common and can spread quickly. Fixing these vulnerabilities can be tricky since all users and dependent projects must upgrade to the patched version, which isn't always done on time. The constant development in Web3 also means , requiring ongoing effort to stay up-to-date. Therefore, developers must regularly test and monitor their code to ensure the system's security and reliability. new vulnerabilities are frequently introduced into the code Identity Management and Fraud Prevention Lastly, identity is a significant concern in decentralized systems. Decentralized applications manage valuable digital assets, such as cryptocurrencies, NFTs, and tokenized assets, which attracts hackers and bad actors looking to steal funds or manipulate the system. Thus, strong identity management is necessary to authenticate users, control access, and detect fraud. This includes using advanced security techniques, such as multi-factor authentication, to prevent unauthorized access to sensitive data. Cloud Solutions for Security in the Decentralized Web So, how can we address these challenges? Scanning for Smart Contract Vulnerabilities One solution is to scan Smart contracts and code for vulnerabilities, possible credentials leaks, and misconfigurations. Cutting-edge scanning techniques can detect vulnerabilities, potential credential leaks, and misconfigurations in Smart contracts and code. The detection process is highly automated and efficient, ensuring it never slows down application operations. Additionally, developers can use static analysis tools to identify and fix code vulnerabilities before deploying the code. Strengthening Identity and Access Management (IAM) Another solution is strengthening IAM (Identity and Access Management) for cloud environments by providing visibility, control, automation, and governance of entitlements and user access. This includes continuous monitoring and automated remediation. By monitoring user activity, security teams can quickly identify and respond to potential threats, preventing data breaches and other security incidents. Providing Visibility into Web3 Applications We can also provide visibility into web3 applications running on permissionless networks. For instance, tools can detect real-time threats, anomalies, and policy violations across the decentralized infrastructure. By monitoring network traffic and user behavior, security teams can quickly identify and mitigate potential threats, ensuring the integrity and security of the system. Cloud-Native API Security Cloud-native API security is a crucial aspect that we specialize in, utilizing advanced AI/ML techniques. Our solutions incorporate machine learning and artificial intelligence to identify and prevent API-based attacks, including injection, brute force, and account takeover attacks. By analyzing network traffic and user behavior, we can quickly identify and respond to potential threats, preventing data breaches and other security incidents. Regular Auditing and Monitoring Regular auditing and monitoring of cloud infrastructure are crucial to detect security threats and vulnerabilities to ensure timely resolution. Security detection and an overall risk score for each cloud asset can be provided to customers. AI and custom business logic can be utilized to identify top-priority items needing correction, making it easier to address critical vulnerabilities and minimize potential damage from hundreds or thousands of findings. By regularly testing and monitoring the system, developers can ensure its security and reliability. Conclusion In conclusion, it's essential to prioritize trust and security in the decentralized web. Blockchain technology's advancements present new and complex security challenges that can lead to substantial financial losses for individuals and businesses alike. By utilizing cutting-edge scanning techniques, strengthening IAM, providing visibility into web3 applications, and utilizing AI/ML techniques, we can help address these challenges and ensure a secure and reliable digital landscape. By continuously testing and monitoring the system, we can stay ahead of potential threats, providing confidence and peace of mind to users and businesses alike.

The Future of Security in a Decentralized World: What to Expect

The COVID-19 outbreak affected people’s lives throughout the globe, every industry, and every economy. After all, it’s a global pandemic for a reason. Throughout history, all crises have forced people to look for new opportunities. Nowadays, this search can encompass anything from a new distribution strategy, amendments in the production process, or the implementation of a new technology. The COVID-19 crisis forced businesses to embrace digital transformation in one way or another. Many companies took advantage of the opportunities brought by digital transformation way before the pandemic happened and can now reap the benefits of being early adopters. On the other hand, some businesses were forced to jump on this bandwagon, as the majority of our daily lives moved to the digital world—remote work, online shopping, online services. Companies have to be creative and innovative to keep their position on the market, but if there’s something positive in this situation, it’s certainly the development the world is undergoing right now. Digital development wouldn’t be possible without technology, so let’s take a look at some of the latest COVID-19 technology trends. Low-Code—The Future of App Development? , 75% of large enterprises will be using at least four low-code development tools by 2024. Low-code development can significantly reduce time-to-market. But there’s more to it than that. According to Gartner Low-code platforms make collaboration between citizen developers, professionals, and business stakeholders much easier. This trend, called democratisation, provides easy access to technical or business domain expertise. While so-called ‘citizen developers’ can easily create apps without having to write much code, professional developers can work on advanced projects, such as AI solutions. Will low-code take over the development world and ? In short, it shouldn’t, because the greatest benefits can be achieved when these two are combined. The domain knowledge of citizen developers together with the advanced programming skills of traditional software developers can lead to functional systems and applications that make it to market much faster. replace traditional programming Focus on Small Scale AI Projects Did you know, that is playing a role in the research being conducted to find a COVID-19 vaccine? The partnership between humans and artificial intelligence is challenging, but it’s also crucial to enable further scaling and adoption of AI. human-AI collaboration The shift from office to remote work is changing employee habits and encouraging companies to explore the possibilities behind data & AI. Cost control can discourage decision makers from investing in large AI projects, but being able to leverage existing data can help you optimise processes and make smarter financial decisions. The rising popularity of artificial intelligence is accelerating the relevance of another upcoming trend. AI Security Challenges More AI solutions mean more potential attacks and users are becoming increasingly aware of the role of security in everyday life. In terms of artificial intelligence, it’s not only about the security of an IoT device. We must also protect AI training data and machine learning models—fortunately, AI can help. Machine learning algorithms can help us understand patterns, distinguish natural communication from phishing attempts, uncover the attacks we may be unaware of, and automate certain cybersecurity processes. According to Gartner, increased amounts of data exposure incidents caused an interesting shift in who we trust. Organizations tend to , so it seems as though interest in AI security will continue to grow. trust algorithms more than central authorities Blockchain is Booming in Logistics In times of crisis, companies are not willing to invest in emerging technologies, but this is not the case when it comes to blockchain. This is because blockchain is widely used in supply chain projects—and COVID-19 has had a significant impact on logistics. The eCommerce industry alone . will grow faster in 2020 than it did in 2019 After an initial slowdown in blockchain projects, and a switch to remote work, companies went back to their blockchain projects, as they promised short-term benefits and are strategically important. All in all, the coronavirus pandemic has proven that blockchain projects bring many advantages to supply chain and logistics projects, such as: Increased efficiency Cost reduction Improved transparency and flexibility , eCommerce will drive more than half of retail sales growth between 2021 and 2024, so we can expect blockchain’s popularity to increase even further. According to analysts Smart Health Devices The global pandemic has severely affected the healthcare industry, causing a lot of disturbance but also the need to provide medical services in a new way. The world has not only been focusing on fighting COVID-19, but also on protecting patients from high-risk groups. Quite often, high-risk patients suffer from chronic diseases which require close monitoring. How can this be done remotely so as not to put them in danger? Smart health devices came to the rescue and this sector is now booming. Wearable devices became more than just fitness trackers. With biosensors, heart rhythm monitors, and even wearable ECG monitors, patients can collect data about their blood pressure, heart condition, respiratory rate, and temperature. Some of these smart devices became helpful tools in the fight against the pandemic. In the longer perspective, they can help scientists or prevent cardiac or respiratory arrest. With powerful possibilities come great challenges. fight Parkinson’s disease In this case, one of the main challenges is, of course, the safety of personal health data and privacy. Companies have to pay the utmost attention to data security, otherwise they may lose their consumers’ trust. What’s Next? These are just a few examples of the technologies that have emerged in 2020, but they’re definitely the ones worth keeping on your radar. It’s certainly much too early to say that a given cutting-edge technology took off due to the coronavirus, but some of the trends are worth keeping an eye on. I highly encourage you to revisit this list in few years from now. Will we rely on artificial intelligence and smart health devices, or will we stick to traditional medical services? Will low-code become more popular? It will be interesting to see which trends will become a part of our daily lives and which will get lost somewhere along the way.

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