Koprocessors Consulting Services

A Good AI Program Must Start with Good Data 1. The National Association of State Chief Information Officers (NASCIO) conducted a survey on the maturity of data governance and enterprise information management in 49 states, with 69% reporting being in the beginning stages of implementing a governance structure. 2. Concerns were raised about the potential harm of using messy data in generative AI systems, as it can lead to unfair allocations of resources and wasted funding for ineffective programs. 3. The survey also revealed that 84% of states do not have a formal data literacy proficiency program, highlighting the need for effective integration of data across multiple agencies. 4. To unlock the full potential of generative AI in the public sector, experts recommend building a government that speaks the language of data, giving data officers a voice in procurement, creating data policies and standards for AI use, and conducting regular data audits and readiness assessments. 5. Experts stress the importance of involving diverse voices in discussions and decision-making around data governance, and caution against being swayed by the hype of AI without understanding the data that goes into it. Starting with a well-defined and feasible use case is recommended for a successful pilot project.

*Global Data Intelligence & Governance Market Report - A $24.73 Billion Market in 2023* The global data intelligence & governance market is anticipated to reach US$24.73 billion in 2023, growing at a CAGR of 13.62% during the forecast period. Source: https://lnkd.in/dSk5aDbG

Career in Data Analytics: Which countries are the best for you? 1. The field of data analytics is brimming with potential and offers intellectual challenges and lucrative salaries. 2. The United States is the undisputed heavyweight in the data analytics world, with a thriving ecosystem of tech giants, startups, and Fortune 500 companies. 3. Canada is a rising star in the data analytics scene, offering a friendly and multicultural environment with a government that actively supports the tech sector. 4. Singapore is a small but powerful player in the data analytics arena, with its strategic location, robust infrastructure, and government initiatives attracting tech companies and professionals. 5. Beyond the big names like the US and Singapore, emerging economies like India, Brazil, and China are experiencing a surge in demand for data analytics talent, making them potential goldmines for career-driven individuals. Source: https://lnkd.in/dS26NhJh

ChatGPT Now Allows Users to Bring Multiple AIs Into Conversations 1. OpenAI introduces ChatGPT feature for better decision making and creativity. 2. Users can now add multiple GPT chatbots to existing conversations. 3. The feature allows for custom chatbots to interact with each other. 4. GPTs from OpenAI's GPT Store can be added to conversations. 5. The feature does not support group chats, but users can create custom GPTs for specific discussions. Source: https://lnkd.in/dyQAwPbq

Empowering Fintechs: How AI And Data Lakehouse Is Redefining Data Dynamics? 1. Fintech companies are facing a growing need for predictive analytics capabilities in order to navigate the dynamic financial markets. 2. The Data Lakehouse, a unified data platform that combines the expansive storage capabilities of data lakes with the structured querying power of data warehouses, is poised to redefine how financial data is managed and analyzed. 3. The convergence of Artificial Intelligence (AI) and Data Lakehouse is revolutionizing the financial industry by providing a powerful tool for harnessing the potential of data. 4. The Data Lakehouse not only consolidates data, but also offers cost savings, increased flexibility, and the ability to deploy advanced solutions such as fraud detection and recommendation engines. 5. The synergy between AI and Data Lakehouse signals a new era of data innovation, making it an imperative for fintechs to adopt this technology in order to sustain success in the rapidly evolving financial landscape. Source: https://lnkd.in/gBh6UZfU

Create news directly from analytics of large data sets – ‘data journalism’ & AI is here 1. Tom Snyder, executive director of RIoT, joins WRAL TechWire's list of top contributors 2. The article discusses the trend of "data journalism" and how it is becoming more prevalent in the industry 3. Data analysis has been a part of journalism for a long time, but now technology allows for larger data sets to be analyzed and used for news stories 4. The process of data journalism involves finding, cleaning, visualizing, publishing, distributing, and measuring data sets 5. The next step in digital transformation for journalism may involve automation of news stories using large data sets and generative AI.

Building and Protecting the Value of Data Assets in 2024 1. Data is becoming increasingly important and valuable for organizations. 2. Three key trends and practices will help organizations increase the value of their data assets in 2024. 3. The first trend is a focus on modernizing data integration processes through AI-infused automation and the use of unified data platforms. 4. The second trend is the integration of historical and real-time data to provide a more complete and timely view for analysis. 5. The third trend is the use of technology to automate data governance and increase data literacy among users. Source: https://lnkd.in/ggA36i8B

The Oil For A Successful AI Machine: Organized, Trusted Data 1. The importance of data in the current era of AI and ML acceleration 2. The challenge of organizing and ensuring the quality of data to effectively train AI and ML models 3. The need for robust data governance practices to address the data conundrum 4. The importance of starting to collect data now for successful AI and ML initiatives 5. Key steps to consider in collecting and managing data for AI and ML, including defining a data strategy, investing in data literacy, and complying with regulations. Source: https://lnkd.in/eywBQCZj

Tired Of Web Scraping? Make The AI Do It 1. Scrapeghost is a new approach to web scraping that utilizes natural language AI to parse and organize web content without the need for page-specific code. 2. The tool relies on OpenAI's GPT API to extract and classify relevant information from web pages, making it easier to scrape and format data. 3. Unlike traditional web scrapers, Scrapeghost allows users to define the specific data they want to extract, making the process more targeted and efficient. 4. The tool is experimental and requires an API key from OpenAI, but it offers useful features and a user-friendly tutorial and command-line interface. 5. Scrapeghost's unique approach to web scraping has the potential to revolutionize the process and make it more accessible for users without coding experience. Source: https://lnkd.in/daZvwyQN

Kids spent 60% more time on TikTok than YouTube last year, 20% tried OpenAI's ChatGPT Source: https://lnkd.in/d4t3jnPx