Trending November 2023 # Top 10 Ai Tools For Academic Research # Suggested December 2023 # Top 15 Popular

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Following is a list of the top 10 AI tools for academic research helpful for researchers

Scholars and Students have devoted countless hours to academic research and writing throughout history. Even though researchers now have access to more information and AI tools than ever before thanks to technology and the internet, it can be challenging to find the right AI tools for research.

Scholars and researchers require assistance sorting through and organizing sources due to the abundance of information available today. In addition, scholars and researchers must write informative, engaging, and well-written articles and reports due to the ongoing pressure to publish. Here is the list of AI tools for academic research.

1. Consensus: 2. ChatPDF:

Users can converse with a PDF document through the AI application ChatPDF. Without signing in, users can interact with any PDF they own, such as books, research papers, manuals, articles, and legal documents. To comprehend the content of PDF files and provide pertinent responses, ChatPDF makes use of a next-generation AI model comparable to ChatGPT.

3. Scite:

Scite’s Assistant, an AI-powered research tool, lets users work together on essays and research papers, find evidence to back up their claims and find evidence to refute them. Clients might enter straightforward questions to get reactions in light of the total texts of exploration distributions. The application can be used by users to find reliable information, search through millions of research articles, and create grant proposals or essay drafts.

4. Elicit:

Elicit, a machine learning tool, is used by the AI research assistant to help automate research procedures. Without specific keyword matches, it can locate relevant articles and extract important information. Inspire may likewise give different exploration exercises, including conceptualizing, summing up, and text-order, as well as summing up central issues from the report that are pertinent to the client’s request.

5. Trinka:

Online sentence structure checker and language proofreader Trinka artificial intelligence was made for specialized and scholastic composition. It is made to catch errors that other grammar checkers miss, like issues with subject-verb agreement, syntax, word choices, the use of pronouns and articles, and technical spelling. In addition, it incorporates a professional tone, the use of technical words, conciseness that goes beyond grammar and spelling, and style guides.

6. Scholarcy:

The online summarizing tool Scholarcy is a simple way to quickly examine and evaluate the significance of documents like articles, reports, and book chapters. Any Word or PDF document can be used to create summary flashcards that are displayed in an organized and easy-to-understand manner.

7. Academic Semantics:

The vast majority know about Google Researcher, which uses Google’s web search tool ability to list academic distributions. But if you’re doing any kind of scientific research, you should try Semantic Scholar. This AI-powered search and discovery tool, made available by publisher partnerships, data suppliers, and web crawls, enables you to keep up with more than 200 million academic publications.


Utilizing the internet to find information is a blessing. The amount of data that is accessible and the fact that it can be found in a variety of formats, such as blogs, essays, films, infographics, and images, present two challenges. Finding and organizing all of the data related to your study’s many areas might take a lot of effort.

9. SciSpace:

SciSpace is a platform driven by AI that lets people read, understand, and submit scientific articles. Its extensive searchable database contains more than 270 million articles, authors, subjects, journals, and conferences. It also offers a variety of paper template choices, a variety of pricing options, and additional services to speed up the printing process.

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Top 10 Project Management Tools For Your Business

blog / Project Management How These Top 10 Project Management Tools Can Help You Streamline Your Workflow

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According to the U.S. Bureau of Labor Statistics, employment for project management specialists is predicted to grow by 7% between 2023 and 2031. It’s no surprise, then, that several aspirants want to enter this promising field. What every project manager needs, however, are the right tools to get the job done efficiently. And finding the right project management software for your team can be a challenging task, especially with the plethora of options available. To make your search a little easier, we have compiled a list of what we think are the top 10 project management tools for you to stay organized and for your team to stay on their tasks. 

In a world where remote work has become increasingly common and teams are spread out over vast geographical distances, a good project management software can mean the difference between teams working efficiently and total unorganized chaos. Project management software can help project managers and the team manage tasks, deadlines, and even budgeting. Let’s explore some of the best ones available on the market.

Types of Project Management Software

Before we get into the list of the top project management tools, it is important to know about the different types of project management software available in the market: 

1. Industry-Specific Project Management Systems

This software has been developed to reduce the customization needs of businesses upon choosing the tools. 

2. Integrated vs. Best-of-Breed Software

Best-of-breed applications specialize in a specific functionality such as task management or scheduling. On the other hand, integrated suite applications combine several functions like task scheduling, creating Gantt charts, and time tracking.

3. Free Project Management Solutions

Free software is usually available for home use or very small teams handling a few projects.

4. On-Site Project Management Software

On-site project management software is present on the company’s in-house servers and is managed by their IT employees. Companies purchase licenses for this software to be used on-site.

5. Online Project Management Software

Online project management software can be accessed as software-as-a-service (SaaS) subscriptions using any Internet-connected device. 

ALSO READ: Interested in Project Management? You Need to Read These 5 Books

Top 10 Project Management Tools

Asana is a dynamic online project management software that helps you map out every minute detail of your project. 


Has a Gantt-style view, the most common graphical representation used for project schedules

Notifies employees in their personalized inbox

Generates detailed progress reports


Provides project timelines 

Offers several integrations

Has a drag-and-drop functionality for tasks 


Free version is extremely restricted 

Not meant for complex projects 


Free to $24.99 per month per user.

Teamwork is one of the best project management tools for teams working on client projects. 


Unlimited clients can be added

Progress tracking for teams 

Visual representation options


Highly customizable

Great invoicing tool

Very user-friendly mobile app


Not great for complex projects

The free plan is only good for small teams


Four types of plans are available—the Free plan, the Starter plan, which is $5.99 per month per user, the Deliver plan, which is $9.99 per month per user, and the Grow plan, which costs $17.99 per user per month.

Jira is an excellent tool which can accommodate every team in your business, including marketing, HR, finance, etc.


Allows you to create and manage unlimited tasks

Standardizes multiple options using automation

Available as an open source for a few projects


Free for up to 10 people

Easy to use


Limited number of software integrations

Challenging to set up


A Free plan is available. Standard plans cost $7.75 per month per user. Premium plans cost $15.25 per month per user. Enterprise plans are also available and cost a minimum of $134,000 annually.


Great analytics and reporting

Centralized communication and document management system

Integrations like Dropbox and Google Drive


Custom integrations

Detailed reporting capabilities

Can add freelancers and third-party agents


Not good for complex projects

No free version

Poor mobile app


The Basic pricing model is $8 per month for each user; the Standard one is $10 per month for each user, and the Pro is $16 per month per each user.

It is one of the most popular project management tools that is especially suited for remote working.


Message boards and to-do lists

File storage

Simple interface


Easy collaborations

Customizable notifications

Free plan


Pricing is not ideal for small teams

No drag-and-drop user interface (UI) capabilities


Basecamp offers two plans—a free Personal plan and a $99 per month plan for Businesses.

It is an intuitive project management tool popular in industries including architecture, interior design, IT, retail, telecommunications, etc. 


Offers Gantt charts

Large tasks can be split into subtasks

Shared file management


Great UI

Can be integrated with email

Free plan 


Poor mobile experience


Freedcamp offers four plans: Free, Pro at $2.49 per month per user, Business at $8.99 per month per user, and Enterprise at $19.99 per month per user.

Wrike is a project management tool that helps users collaborate better and contains several communication, collaboration, and document management tools.


Tasks can be synced to Google Calendar and iCalendar

Visual timelines using Gantt charts

Provides clients with up-to-date information


Better task management

Improved transparency

Free plan for unlimited users


Mobile app needs to be updated

Not user-friendly for beginners


Wrike has five tiers to choose from. Free gives unlimited users access to a limited number of features; Team, which is $9.8 per month for up to 25 members, and Business, which is $24.8 per month for up to 200 members. They also offer Enterprise and Pinnacle tiers. You can contact Wrike to find out about their pricing details.

Kantata is a project management tool that is popular amongst professional service firms and helps users maximize resources across all projects.


Real-time resource management

Project portfolio view

Time tracking


Offers integrated accounting and financial tracking

Project transparency is improved

Several third-party integrations


Needs a simpler UI

Needs an issue management feature


Kantata offers a free trial and pricing starts from $59 per month.

This project management tool for businesses of all sizes is based on several third-party integrations. 


Time tracking 

Resource management 

Team collaboration tools


Free plans for small teams

Interactive Gantt chart

Automated notifications


Requires additional templates


Free for up to three users. Their Premium plan is $4 per user per month billed annually for up to 50 users and their Enterprise plan is $9 per user per month billed annually.

HubSpot is an all-in-one Customer Relationship Management (CRM) tool that provides a variety of features, ranging from marketing to sales, support, and project management.


Collaboration boards

Customer database

In-depth analytics


Great dashboard

Email tracking

Easy to use


Random crashes

Poor automation


It has a Professional Plan which starts at $800 per month, and an Enterprise plan which starts at $3,600 per month per user.

ALSO READ: What is Project Management and How to Become a Successful PM

How to Choose the Best Project Management Software

Ensure the project management tool you choose has the following offerings: 

Advanced features

Great user interface

Online access



Third-party integrations

Good pricing

While our top 10 project management tools will help you streamline your workflow, there is more to it than just the software you choose. You will need the right skills to ensure that you can lead your team effectively. Check out some of the top project management courses from Emeritus to level up your skill set. 

 By Tanish Pradhan 

Write to us at [email protected] 

Best Ai Tools For Digital Marketing

Artificial Intelligence (AI) is impacting every industry we can think of. It is the same with digital marketing. There are some great tools that can help digital marketers in laying out their digital marketing strategies and make the most out of these AI tools in less time. Digital marketers can benefit a lot from using AI tools by saving time and automating repetitive tasks. In this guide, we show you the Best AI tools for Digital Marketing.

Best AI tools for Digital Marketing

If you are a digital marketer and want to make it more productive, you can use the following AI tools to optimize your profession.





Let’s get into the details of each tool and know how to use them.

1] HelloScribe

HelloScribe is an AI writing and brainstorming assistant that can help PR and marketing professionals work smarter and faster without creative blocks or wasted time. You just need to input what you want and HelloScribe can generate endless original ideas and content related to your specific request. You can pick the best of the generated ideas, edit them, implement them in your strategy and publish them on your social media. HelloScribe has tools for creative brainstorming, Brand messaging, Press releases, Headlines, news hooks, media pitches, social media copy, interview questions, etc. You can get more done faster using HelloScribe. You can try HelloScribe for free for 7 days without any credit card and then buy a paid plan if you like its services.

2] Flair

3] Looka

Looka is a great AI tool to design logos for your brand and your clients. On Looka, you can use AI to design the best possible logos for your brand in a few minutes. You do not require any design skills. All you need is a vision of how you want your logo to look. Looka can generate endless options and tweak designs to get exactly what you want. Looka services do not stop with generating a logo, you can also build your brand identity using the brand kit and branded marketing materials that Looka generates. You can choose from 300+ templates that can match your vision and identity. You can customize the design in the easy-to-use editor. To sum up, Looka is a personal designer that can help you design logos and branded content for your clients.

4] is an AI tool that can help you interact with customers and the user community to make your brand more accessible to people. It is the easiest way to connect with the community and look clever, funny, and professional on social media. You can appear smarter and grow your audience with 10x less effort. It is an easy-to-use AI replies generator with extremely simple functionality. You can use chúng tôi on Twitter and LinkedIn and start from a blank page and go to the best content. It also helps you grow better and easier. chúng tôi can help you interact, generate icebreakers for tweets, create viral jokes, and custom reactions. You can try chúng tôi for free using the free plan.

Read: Best AI tools for Content Writing

5] tiledesk

Read: Best Graphic Design Tools and Software for beginners

These are the different tools a digital marketer can implement on their client projects or own projects and make the most out of them.

How AI is used in digital marketing?

AI has different uses in digital marketing. From generating content to interacting with people on social media, and websites, AI can benefit digital marketing easily. All you need is the right tool that suits your need. Even the strategies can be generated by AI tools like HelloScribe. AI can help you get more clients if you are a digital marketer.

What type of AI is used in marketing?

From chatbots to replying to customers to interacting with the community on social media, AI can be used in many ways in marketing. There are many great tools to write marketing copies that convert. You just need to have an idea of how your marketing should be. The rest will be taken care of by the AI.

Related read: 10 Online jobs that you can do from Home.

Top 10 Machine Learning Frameworks For Ai & Ml Experts

Machine learning frameworks play a crucial role in developing and deploying artificial intelligence and machine learning models. They provide a comprehensive set of tools, libraries, and resources that enable AI and ML experts to build robust, efficient, and scalable solutions. This article will delve into the top 10 machine learning frameworks that every AI and ML expert should be familiar with. From industry giants to emerging contenders, these frameworks empower professionals to tackle complex challenges and drive innovation in AI and ML.


Developed by Google Brain, TensorFlow is one of the most popular and widely adopted machine learning frameworks. Known for its flexibility and scalability, TensorFlow provides a comprehensive ecosystem for building and deploying machine learning models across various platforms and devices. With support for high-level and low-level APIs, TensorFlow offers AI and ML experts a wealth of tools and resources.


PyTorch has gained immense popularity among researchers and practitioners due to its dynamic computational graph and intuitive Python interface. Developed by Facebook’s AI Research lab, PyTorch provides a flexible and expressive framework for building and training deep learning models. Its emphasis on simplicity and usability makes it a top choice for prototyping and experimenting with new AI and ML ideas.


Based on TensorFlow, Keras offers a user-friendly and intuitive interface for building and training deep learning models. Known for its simplicity and ease of use, Keras enables AI and ML experts to iterate and experiment with different architectures and hyperparameters quickly. With its focus on rapid prototyping, Keras has become a go-to framework for beginners and experienced practitioners alike.


Scikit-learn is a versatile and widely used machine learning library in Python. It provides a rich collection of algorithms and tools for data preprocessing, feature selection, model evaluation, and more. With its comprehensive documentation and straightforward API, scikit-learn is an excellent choice for implementing machine learning techniques and workflows.

5.Microsoft Cognitive Toolkit (CNTK)

The Microsoft Cognitive Toolkit, or CNTK, is a robust deep learning framework offering high performance and scalability. Developed by Microsoft Research, CNTK supports distributed training across multiple GPUs and machines, making it suitable for large-scale AI and ML projects. Its rich features and support for various programming languages make it a valuable tool for AI experts.


Theano is a popular Python library that allows for efficient computation and optimization of mathematical expressions, especially in deep learning. It provides a flexible and efficient framework for building and training neural networks, and its symbolic expression capabilities enable automatic differentiation and GPU acceleration.


MXNet is a flexible and efficient deep learning framework that supports multiple programming languages, including Python, R, and Julia. Known for its scalability and performance, MXNet allows AI and ML experts to build and deploy models across various devices and platforms. Its modular design and support for dynamic and static computation graphs make it a powerful tool in the machine learning ecosystem.


Caffe is a deep learning framework focusing on speed, modularity, and expressiveness. With its pre-trained models and easy-to-use interface, Caffe is well-suited for tasks such as image classification, object detection, and segmentation. It provides a comprehensive ecosystem for training and deploying deep neural networks, making it a popular choice in computer vision and other domains.


Torch is a scientific computing framework that strongly emphasizes deep learning and GPU acceleration. Built on Lua, Torch provides a flexible and efficient platform for training and deploying neural networks. Its ecosystem includes powerful libraries such as NN for building neural networks and image processing, making it a preferred choice for researchers and AI practitioners.


Watch Out For The Top 10 Ai Startups Leading The Ai Race In 2023

These top 10 AI startups are revolutionizing the technology market in 2023

There are multiple AI Startups that through their innovation and improving technology are solving problems at a pace never seen before. And there seem to be no breaks to these developments in the AI industry by these startups. From providing healthcare services to presenting highly intelligent AI and ML solutions to almost every sector, AI startups are the hottest brands in the market. Here is the list of top 10 AI startups leading the AI race in 2023.

UBTECH Robotics

Chinese AI and humanoid robotic company Ubtech Robotics recently introduced Ubtech’s educational robot Alpha Mini into local kindergartens to help further artificial intelligence education for preschool children. This project is targeted toward children aged 3-5 and will cover 300 nursery centers in Seoul. UBTECH Robotics, a developer of intelligent humanoid robotics and AI technologies, has unveiled Walker X, the latest version of its groundbreaking bipedal humanoid robot. It is another step closer to becoming the gold standard in humanoid robotics.

UISEE Technology

Autonomous driving technology company UISEE and the Guangdong Airport Authority have jointly unveiled a “Smart Logistics Laboratory” and the launch of an unmanned tractor project. This project introduced five unmanned tractor models from UISEE, designed to replace manual transportation on the outbound business lines of domestic cargo terminals, as well as the inbound and outbound business lines of international cargo terminals. Teksbotics & UISEE jointly pilot new package delivery solutions using a self-driving vehicle to design and build a cost-effective autonomous delivery vehicle for the last mile delivery.


UiPath fourth-quarter results topped estimates, guidance for 2023 was disappointing, and the stock finished March down 38%. It has provided four reasons for the guidance: Russia, FX headwinds, general macro concerns, and a sales leadership transition. UiPath and DocuSign, both companies will generate significantly slower growth this year and also face near-term margin pressure.


Uniphore Technologies Inc, a conversational automation platform, on Wednesday said it has acquired an artificial intelligence (AI)-powered knowledge automation solution company Colabo. To help IVAs and live agents deliver better customer interactions. This acquisition brings together unique capabilities to arm enterprises with new tools that provide a quick resolution to consumer queries and empower agents with real-time, actionable information


Uptake is the industrial analytics platform that delivers products to major industries to increase productivity, security, safety, and reliability. Uptake is a World Economic Forum Technology Pioneer and three-time CNBC Disruptor 50 honoree. It helps industrial companies digitally transform with open, purpose-built software that delivers outcomes that matter and industrial companies are once again the creators of economic growth and opportunity.


Vast Data combined its all-flash, high-performance storage with Vertica’s Eon Mode Architecture to give data warehouse-like responses to data lakes in a converged product. Nvidia had increased its investment in storage startup Vast Data, it was not exactly clear how or if the companies already were working together.  The companies announced a few weeks ago during Nvidia’s GTC Spring event that Nvidia Bluefield DPUs are powering Israel-based Vast Data’s new Ceres storage platform.


Vectra AI, a leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises, today released the findings of its latest Security Leaders Research Report. This alarming statistic comes as cyber threats increase and security and IT teams face mounting expectations to keep their organizations protected from such threats. Now AttackIQ and Vectra joined together to help customers enable a proactive, threat-informed defense.


VerbIT is a Tel Aviv- and New York-based AI transcription & real-time captioning solution which provides the highest accuracy & fastest transcription models that have acquired Take Note in the UK. This acquisition marks VerbIT’s entrance into the market research space and increased presence in Europe. VerbIT has recently started paying its transcribers and reviewers even less money than before. The rate for editing was 30 cents per audio minute, it is currently 24 cents or even less on occasions for a standard job.

WeRide YITU Technology

Chinese artificial intelligence company, Yitu Technology is considering an initial public offering in Hong Kong after tightening regulatory scrutiny stalled an earlier attempt to list in Shanghai. Yitu, whose application for a Starboard IPO was withdrawn last month, could file for a listing as soon as later this year. YITU has obtained a number of authoritative international standards certifications for information security and privacy protection, including ISO/IEC 27701:2023 and ISO/IEC 27001:2013. ISO/IEC 27701:2023, which is the world’s strictest.

Biotech And Pharma Bet On Ai For Drug Development And Research

Exploring Possibilities for AI and ML for Drug Discovery  

Developing new medicines is not for the faint-hearted! On average, it takes about a decade of research with an expenditure that amasses US$2.6 billion to Out of the total drug discovery done only about 5 per cent of experimental drugs make it to market! This paves way for drug makers and pharma companies to invest hugely in artificial intelligence and machine learning with the hope that these technologies will make the

Machine Learning Applications at Biopharma Companies

The high prices of the drugs are attributed to the significant costs of drug research and development, done by the pharma giants. This figure has recently been estimated to average around UD$2.6 billion per treatment. It takes up to 15 years to bring a new therapy to market. Less than 12% of drugs that enter clinical trials end up being commercialized, leading to pharma’s and investors turning their gaze to making drug discovery a faster process in the recent times especially post Covid-19 aftermath. Artificial Intelligence (AI) has recently been earmarked as a debated topic of interest in the area of

Fostering Global Pharma Alliances

Several prominent AI and ML companies bog and small have focused some of their resources to address the inefficiencies of this space-

Developing new medicines is not for the faint-hearted! On average, it takes about a decade of research with an expenditure that amasses US$2.6 billion to shepherd an experimental drug from lab to market . The field of artificial intelligence and machine learning (AI/ ML) has witnessed sharp upturns, particularly concerning deep learning (DL) methods that are pillared with the availability of big data. Biomedical data is humongous and becoming increasingly available in ML-ready digital formats, it is now possible to deploy AI/ML algorithms to support h ealthcare research and services . However, within the larger healthcare ecosystem, biopharmaceutical companies, in particular, have been criticized for the skyrocket pricing of prescription drugs. Artificial Intelligence and Machine learning have the power to improve drug discovery and medical research which may reduce drug prices in the chúng tôi paves way for drug makers and pharma companies to invest hugely in artificial intelligence and machine learning with the hope that these technologies will make the drug discovery process faster and chúng tôi high prices of the drugs are attributed to the significant costs of drug research and development, done by the pharma giants. This figure has recently been estimated to average around UD$2.6 billion per treatment. It takes up to 15 years to bring a new therapy to market. Less than 12% of drugs that enter clinical trials end up being commercialized, leading to pharma’s and investors turning their gaze to making drug discovery a faster process in the recent times especially post Covid-19 aftermath. Artificial Intelligence (AI) has recently been earmarked as a debated topic of interest in the area of medical care . Biopharmaceutical industries are putting their efforts to expand their viewpoint in AI to enhance the drug discovery process, diminish failure rates in clinical trials, generate superior medicines and reduce research and development expenses. Accessibility of methodological statistics in life sciences coupled with speedy developments in machine learning algorithms has led to an evolution of AI-based start-up companies focused on drug discovery over the recent years.Several prominent AI and ML companies bog and small have focused some of their resources to address the inefficiencies of this space- • Pfizer , has partnered with IBM Watson to identify more robust targets during the discovery phase, process thousands of scientific publications to determine novel combinations of drugs for improved efficacy, and optimize the patient selection for clinical trials. • Insilico Medicine and Exscientia , are attempting to utilize genomics and artificial intelligence tools for computational design of new drug candidates. If the integration of AI into the drug discovery and design process works, it can have incredible disruptive effects. It could disrupt the entire drug discovery ecosystem throwing many chemoinformatics out of jobs. However, cutting down drug discovery from years to months especially after Covid-19 pandemic would mean an incalculable effect on the larger pharma environment. An industry which justifies its high drug prices by the lengthy and costly research undertaken at the development phase, it ‘ll be a tectonic shift, that seems like a gamble worth taking.

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