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How to use Perplexity AI for research and data analysis

If you would like to improve your research and data analytical skills, you might be interested in learning more about Perplexity AI. An artificial intelligent (AI) research tool that offers an alternative to traditional search engines like Google and chat-based editors like OpenAI's ChatGPT. It aggregates information from various sources across the web to provide comprehensive answers to user queries. This tool is particularly useful for detailed research, academic writing, and problem-solving, offering features such as source verification, language model selection, and the ability to generate and organize content. Ever found yourself drowning in a sea of tabs, each one a different source of information for your research project? It's a common problem that many of us face. But what if there was a tool that could aggregate all that information and present it in a comprehensive, easy-to-digest format? Meet Perplexity AI, your new best friend in the world of research. One of the key strengths of Perplexity AI is its ability to pull information from multiple sources, including the web, YouTube, and Reddit, when you input a query. This allows the tool to deliver detailed, well-sourced answers that go beyond the capabilities of traditional search engines. Additionally, Perplexity AI allows you to ask follow-up questions, allowing you to dive deeper into a topic and obtain more nuanced insights. Perplexity AI offers a range of features that set it apart from other research tools: Here are a selection of other articles from our extensive library of content you may find of interest on the subject of Perplexity and alternative to Google Search : Perplexity AI is particularly beneficial for academic research, as it can search reliable academic sources for papers and studies, providing you with credible information to support your work. It is also valuable for problem-solving, offering step-by-step solutions to technical issues, making it a useful resource for both students and professionals. In terms of content creation, Perplexity AI can help you generate structured content and pages that you can easily share with others. This is especially useful for bloggers, writers, and content creators who need to organize their work efficiently and effectively. Perplexity AI offers several advanced tools that further enhance its capabilities: Perplexity AI offers a user-friendly interface that simplifies the research process by summarizing information and allowing you to ask questions and receive detailed answers quickly. This makes it easier to gather and understand complex information, enhancing your productivity and efficiency. However, it is important to note that while Perplexity AI offers many advanced features, its image generation capabilities are pretty much non-existent when compared to OpenAI's DallE 3 and Midjourney. Additionally, some features, such as advanced image generation, may require a Pro version, which could be a limitation for some users who are short on cash. Perplexity AI is a robust and versatile tool for research and content creation, offering comprehensive answers, source verification, and a range of advanced features. Its ability to aggregate information from diverse sources and provide well-sourced, detailed responses makes it particularly useful for students, researchers, and content creators looking for a streamlined way to gather and organize information. With its user-friendly interface and array of capabilities, Perplexity AI is a valuable resource for anyone navigating the complexities of the digital age.

Geeky Gadgets

Sat, 13 Jul, 6:00 AM UTC

The Best Generative AI Workplace Productivity Tools

By now everyone's probably seen generative AI tools like ChatGPT and Midjourney that can create text, drawings and even computer code that look like they've been made by humans. They're highly impressive, but are you just using them for fun, or have you worked out how to get them to do something that's truly useful? Well, one of the areas where they have the most potential is automating day-to-day workplace tasks. In the last two years, many new apps, tools and services have appeared that can help us become quicker and more productive at work. So here's my roundup of what I believe are some of the most impressive, useful or innovative generative AI productivity tools available today. They can help anyone to do their job quicker or more efficiently, saving valuable time that can be spent on more rewarding and creative tasks. These are in no particular order, but let's start with five that I think are particularly interesting or noteworthy: Zapier Zapier is an integration tool, which means it helps other tools and applications talk to each other and work collaboratively. For example, it can be used to automatically log information from sources like call logs, emails, or chat transcripts and used to create to-do cards in project management tools like Trello, calendar events, or update records in CRM software like SalesForce or Hubspot. This can save users huge amounts of time that would be spent copying and updating records across different platforms. It also reduces the chances of human error. Zapier has now integrated generative AI chatbots that make this process as simple as telling them what you want it to do. It will automatically find the right connectors and triggers, and pull out insights from real-time business data, This makes it simple for anyone to build AI workflows involving multiple applications and data sources. Otter.ai In recent years, Otter has emerged as one of the leading AI-powered meeting assistants. It can automatically create transcripts of conversations that can be organized and searched, as well as extract insights and action items. It integrates with popular messaging and meeting apps like Zoom and Teams and can generate email summaries and send them out to relevant people while keeping track of any follow-ups that are needed. One of the things that set it apart is its high level of user-friendliness, meaning that even colleagues who are nervous about trying out new tools should be able to start making use of its AI features very quickly. Trello Millions of people use project management tools to keep track of ongoing work or measure progress toward goals, and Trello is one of the most popular. Like many industry standard tools, it's recently been powered up with the inclusion of generative AI features, in this case provided by the Atlassian Intelligence engine. This streamlines the process of creating new cards by generating content and automated summaries, as well as even suggesting improvements for grammar or clarity when communicating your ideas. Atlassian Intelligence is only available to premium and enterprise Trello users at the moment but may be integrated into the free version in the future. Zoom With AI Companion Zoom established itself as an everyday tool during the COVID-19 pandemic, helping many companies carry on with business (almost) as usual. Many more of us discovered it was also a great way to keep in touch with family and friendship groups. More recently, it, too, has received a generative AI makeover thanks to the addition of Workplace Companion. With this, users with a paid-for subscription can create automated summaries of calls and virtual meetings, along with follow-ups, assignments and action points. This eliminates the need to take notes and other manual administrative actions during meetings and lets attendees focus on the discussion at hand. BeeDone BeeDone takes a different approach to many of the productivity apps here by gamifying the process of task management. It does this by breaking complex tasks down into simple steps and then awarding points for completing them. It's a fun idea that adds a new spin on the numerous "smart" to-do lists, task managers and time trackers that are available. BeeDone learns users' habits and fine-tunes its ability to optimize processes and even includes "productivity tournaments" where users can compete against each other to see who can become the most efficient! There are many more tools that let anyone put generative AI to work to streamline routine workday tasks; here are some more of the best that I've come across: Asana Automate project management and workflow tasks and manage calendars. Avoma This AI meeting assistant transcribes meetings but also provides coaching insights to help users improve their communication and engagement skills. Beautiful Transform ideas into fully realized slides and presentations with automated design features. Clara Clara is an AI assistant that aims to act as a virtual employee, scheduling meetings, communicating between attendees and adding details to your calendar once they've been established. ClickUp Generative AI-driven workplace productivity suite with project management, time tracking, whiteboarding, agendas and other features. Clockwise Time-management tool that can automate scheduling to help teams make more efficient use of their time. Decktopus Generate slide decks and presentations from natural language prompts. Duet Another Google service, this one, is built into Workspace to provide a collaborative assistant for productivity tasks. EmailTree Email management and customer service platform with features like automatic reply suggestions, multilingual support, team management, CRM, sentiment analysis, and automation. Fireflies Transcribe, summarize and search voice conversations. Gamma Automates the creation of presentations and various types of documents with the help of generative AI. Mailbutler Integrates with common email applications to provide tools that automate composing, summarizing and responding to emails. AI-powered workspace that manages tasks as well as offers functions like document summarization and content creation. Reclaim AI-powered calendar management and time tracking. Sanebox AI-powered email management that analyzes incoming mail, sorts it into relevant folders and generates reminders and auto-responses. Tome Leverage AI storytelling to create compelling decks and presentations using GPT-4o technology.

Forbes

Tue, 16 Jul, 6:00 AM UTC

Council Post: What Does AI Mean For The Future Of Insights And The Market Research Industry?

Abigail Stuart, with 20+ years in brand and market research, drives innovation and champions AI. Connect on LinkedIn. I've been working in market research for my entire career spanning a 30-year period, including leading large teams and building my own successful agency. I'm someone who is curious and open to change, so I've always tried to stay at the forefront of innovations, playing an active role in shaping our industry. But if I'm completely honest, not a lot has changed in the world of market research over that period. The biggest shift came with the arrival of the internet and the wholesale shift of market research surveys being conducted online, capitalizing on speed, reach and cost savings. However, research methodologies are pretty much the same today as they were 30 years ago -- we gather people's opinions by asking them about their past behaviors, attitudes and needs via surveys, interviews and focus groups. Sometimes we use mobile devices and virtual platforms to speak to people, but the instrument and design remain pretty much unchanged. Then along comes generative AI (GenAI) in the form of large language models such as ChatGPT 4.0 and other tools capable of generating human-like output in text, visual and audio forms. I predict with absolute certainty that GenAI will fundamentally change the way insights are generated -- in fact, it is already offering unprecedented opportunities for innovation. But the big question is where, as leaders, can we start to harness the power of GenAI for insight generation? I'd like to put forward a scenario planning framework to take us on an AI innovation journey, starting with leveraging new technologies to enhance current practices, moving to the creation of new methodologies, then toward a paradigm shift to radically redefine how insights are generated. There are a lot of mundane tasks to complete in a market research project -- from fieldwork updates, data cleaning and proofreading and other aspects of quality control. All of this is important, but it adds to the cost while reducing time for interpretation and storytelling. This scenario is an easy first win for insight leaders, with a focus on leveraging GenAI to make market research processes more efficient. Insight leaders need to prepare to automate up to 80% of what they do -- because if they do not, someone else will and they will lose competitiveness. Key aspects include faster turnaround, reduced manual effort, automation of repetitive tasks, and improvement in data processing speeds. For example: In this context, AI is applied to existing datasets to enhance its strategic value. It helps companies extract more value from the vast digital datasets they collect -- data that is often unstructured and complex, making it difficult to process and analyze using traditional methods. For example: In this scenario, the focus shifts to transformational innovation. The major shift to prepare for is a move away from traditional surveys that collect opinions via closed questions and rating and ranking scales to undertake "qualitative research at scale." GenAI, with its ability to understand, generate and manipulate human language, will transform qualitative research by making it scalable in ways previously only applicable to quantitative methods. Imagine a client calls you on Friday afternoon needing urgent insights into their new global ad campaign by Monday morning. They want quantitative data for confident decision-making, but they also want rich qualitative insights from consumers across multiple markets. With GenAI this is now possible, here's how: In this scenario, GenAI will be used not just to analyze data but to foresee and shape future market landscapes. In this transformative quadrant, we are only limited by our own imaginations of what is possible. The potential applications of AI are vast: We are at a pivotal moment for the market research industry. If we embrace GenAI and drive toward transformational innovation, the industry will continue to thrive. If we fail to adapt, we risk technology disruptors infiltrating our sector and pushing seasoned professionals to the sidelines. Start small, but act today by embracing GenAI to make market research more efficient through automation. Then shift your attention to augmenting existing methodologies with new tools for data collection and analysis. Keep an eye on the grand prize, where AI transforms insights generation into an always-on service, generating real-time insights from real and synthetic data, with the ability to predict consumer behavior to inform investment decisions. By staying curious, open to change and committed to continuous learning, we can harness AI's full potential and lead the market research industry into a new era of excellence. Forbes Agency Council is an invitation-only community for executives in successful public relations, media strategy, creative and advertising agencies. Do I qualify?

Forbes

Wed, 17 Jul, 12:02 PM UTC

Council Post: The Evolving Role Of Technology In Market Research

Recent advancements in generative AI and machine learning are changing the ways data analytics and market research are conducted. Practitioners and consumers of market insights can leverage new algorithms to develop deeper insights faster than ever. But these technologies are not immediate problem-solvers. Firms must understand the best marketing applications of generative AI to harness their full potential -- responsibly freeing practitioners from repetitive tasks and enabling them to focus on higher level tasks. How is AI affecting market research? Traditional analytics has historically been used to perform statistical analysis on large collections of data. While helpful, it is primarily retrospective in nature. These data points -- which rely on static models -- lack the capability to generate new insights or help predict future changes. In a dynamic economy, focusing on past performance may be a disadvantage. Generative AI models such as ChatGPT are trained on massive databases of information but those databases are not infinite, so chat models aren't always responsive to the context you want them to work in. This leads to "hallucinations," which produce errors. The best way to secure the benefits of AI while eliminating risks is to work with experts who maintain your system. Humans are still best at identifying bias, ethics and privacy issues. For teams that put too much trust in tools built on external data, their successes are at constant risk of mistakes due to lack of human oversight. Instead of trusting their sensitive data to public databases, many teams opt to build their own AI for research purposes. An internal chatbot can be specifically trained on your data, eliminating bias and most hallucinations from the system. Plus, training on internal data enables you to ask questions like, "What was the competition like between these two major soda brands between 1990 and 1995, and which marketing campaigns affected the results the most?" These types of questions provide powerful insights that could not be derived from a public AI. Most businesses know they want to invest in AI for some of their data analysis. A more productive question is whether they want to build their own product or partner with an AI company. To understand the best decision for your firm, consider how these traditional challenges in market research will change with new technology developments. One of the most important tasks in market research is data cleaning. As analysts, we must ensure our data is based on valid responses. This has always been the case with data analytics -- you get out what you put in -- but is even more critical in the age of artificial intelligence. If your firm creates and interprets data from a large number of surveys, you already know this is an arduous task when performed manually. As a result, many firms are tempted to outsource all of their data cleaning to an AI solution. While this is a great application of AI, excessive trust in algorithms risks missing mistakes in data which can result in exponentially worse errors. Many firms prefer working with companies that emphasize high quality data collection to mitigate this risk. They seek partnerships with companies that specialize in using AI to identify large blocks of text for efficient human screening. This saves a lot of time in the process of data cleaning while upholding the importance of human insights. An ideal partner will have a deep understanding of how generative models should (and should not) be used for data cleaning. If you are approaching the development of your own AI product, this should be considered with your internal team. Do you have the capacity to maintain a significant level of focus on data cleaning? If not, a partnership with the right firm may be in your best interest. Survey insights have traditionally been limited by quantitative analysis. For example, in a standard survey for a banking service, you may ask participants to rate the service on a scale of one through 10. But what do these data points tell you about your business? More often than not, firms must arrange follow-up qualitative interviews. This deeper dive with respondents yields meaningful insights at a steep cost, both of time and money. Instead, with a properly trained AI model, you can design your survey to include interactive elements that prompt qualitative responses. For example, if a respondent gives a score of 90%, which we know falls at the high end of the Net Promoter Score, a properly trained chat feature can ask a follow-up question and probe further if needed, diving deeper into what an individual customer likes and dislikes about your service. You may find that loyal customers have problems with your company, allowing you to revisit your strategy in a more proactive manner. To set this up properly, you need to either partner with a company who has expertise in training AI models or have the capability to hire experts for your team as required. Data cleaning is even more important when using surveys with qualitative elements. This further emphasizes the importance of your dedication to maintaining data quality. If you plan to include qualitative chat elements in your otherwise quantitative survey, it is important to work with experts that understand how to use machine learning with very large data sets. This skillset extends far beyond expertise in chatbot functionality. If you want AI to perform both data cleaning and qualitative functionality in your customer surveys, you may want to partner with a market research company with expertise in artificial intelligence. The specialized knowledge required is often too much for an internal team to assume. Plus, working with a trusted provider helps mitigate risks -- and liabilities -- of working with these new and powerful technologies. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?

Forbes

Wed, 17 Jul, 8:02 PM UTC

Top 8 AI Tools for Legal Professionals

According to a 2024 generative AI report, the adoption of AI in the legal profession shows that 14% of law firm and corporate legal respondents are already using AI technology, 12% are planning to use it, 35% are considering whether or not to use it, and 40% currently have no plans to use AI. Additionally, 27% of legal industry respondents said they use open-source AI tools like ChatGPT today, while 43% plan to use legal-specific AI tools within the next three years. Here are a few AI tools for legal professionals to explore. Casetext Casetext, one of the best legal research tools on the market, and its new AI assistant has the potential to make it even more useful. Casetext speeds up the research process with its AI assistant called CoCounsel, which was developed in collaboration with OpenAI and built on top of GPT-4 with customizations for the legal industry. Casetext claims that CoCounsel can write and comprehend at a postgraduate level. Beyond legal research, CoCounsel can also help with reviewing documents, searching databases to discover relevant information, preparing for trial, summarising findings, and laying out the basics for a legal memo. Detangle.ai Detangle makes innovative use of AI technology to summarise lengthy legal research and transform complex jargon into plain English. By simplifying and explaining legal terminology, detangle helps one save thousands in legal fees and boost one's confidence in legal matters. The detangled document provides a concise 1-2 paragraph summary, so one can immediately understand the key points. With a simple interface, one can upload assets or paste URLs to get AI-generated summaries of lengthy documents, audio files, or videos, making complex legal jargon easy to understand. Amto Amto utilises 692 proprietary AI algorithms specifically trained for lawyers, to enhance online visibility, attract quality leads, and convert them into loyal clients. Amto combines human expertise with AI for superior legal marketing; expert lawyers curate content, while AI selects ideal keywords to target the audience effectively. It ensures all strategies comply with ABA guidelines, safeguarding the integrity of one's practice. The services include using generative AI based on ChatGPT for drafting legal documents, letters, and emails, providing instant revisions, recommending missing clauses, identifying research gaps, and creating client reminders for deadlines and important dates. AI Lawyer AI Lawyer is an innovative tool designed for everyone. It avoids expensive legal consultations, long waits for appointments, and confusing legal texts. It provides legal information and simplifies legal language for general audiences, supports lawyers in legal research and strategy development, and helps law students hone their research skills and gain insights into modern legal trends. AI Lawyer's best features include providing fast, easy-to-understand insights into complex legal issues, summarising uploaded documents, and creating simple legal agreements in minutes. Lawgeex Lawgeex contract review automation solution, powered by patented AI technology, reviews and redlines legal documents based on one's predefined policies. Unlike other solutions, Lawgeex comprehends contractual context and one's position, ensuring consistency across contracts, saving time and money, and expediting deal closures. This AI-driven tool supports high-volume contract analysis for non-disclosures, service agreements, and more. It integrates with popular CRM systems and other apps, allowing for automatic redlining via email or direct integration, making the review process efficient and seamless. Lex Machina Lex Machina, a legal analytics company owned by LexisNexis, leverages AI technology to review and sort court documents, enabling users to discover trends among parties, lawyers, judges, and courts. The data includes findings, damages, and case outcomes. Lex Machina continuously crawls databases such as the USPTO, ITC/EDIS, PACER, and state court data every 24 hours, ensuring the AI platform has access to the latest information on millions of cases. This comprehensive data collection allows Lex Machina to deliver a vast array of AI-driven insights. Law.co Law.co (AI) platform for lawyers and law firms, is designed to digitise and optimise legal operations. It automates and streamlines complex legal processes and research, while enhancing contract drafting and editing with the power of GPT. This powerhouse platform leverages AI to revolutionise law firms' operations, offering cutting-edge features like automated legal drafting, contract review, and enhanced legal research. Law.co also utilises GPT and an advanced semantic search engine, providing powerful access to queries with contextual understanding and continuous learning capabilities. Additionally, the platform is multilingual, making it an excellent choice for firms offering services in multiple languages. Harvey AI Harvey AI stands among other AI-driven legal tools for its predictive abilities. It dissects extensive legal databases, delves into case histories, and analyses legal trends to provide well-informed predictions about case trajectories. This enables proactive decision-making by leveraging data-driven insights, setting it apart as a distinctive advantage. Harvey AI's ability to detect early warning signs and suggest risk-mitigation strategies can revolutionise internal procedures. It goes beyond reactive legal actions, empowering organisations to make proactive decisions, a feature that marketers can highlight to showcase its unique benefits.

Analytics India Magazine

Fri, 19 Jul, 8:00 AM UTC

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