Generative AI Tools

Introduction To Generative AI Tools

Vidhi Gupta
July 11th, 2024
31
5:00 Minutes

Best Generative AI Tools

The best generative AI tools have the potential to cater to many different professional and creative needs. Each tool offers unique features, potential drawbacks and pricing structures. These are fit for both professional and personal uses.

OpenAI GPT-4

GPT-4 is the name of an advanced language model. It has the ability to understand and generate highly human-like text as per the given input. It's widely used for multiple applications. These include content creation, chatbots, summarization and translation. Here are the pros, cons, and price of OpenAI GPT-4.

  • Pros

Versatile Applications: It is apt for multiple industries and tasks.

High-Quality Text Generation: It produces contextually relevant and coherent text.

Robust API: It integrates easily into workflows and applications.

  • Cons

Contextual Memory Limitations: It somewhat struggles with maintenance of context over long conversations.

Costly: Its pricing can make it unsuitable for extensive use.

Ethical Concerns: Risk of generating inappropriate or biased content.

  • Pricing

Begins at $0.06/ 1,000 tokens. Higher usage tiers are also available.

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Google DeepDream

DeepDream by Google is a computer vision program. It employs convolutional neural networks (CNNs) to create and improve dream-like and surreal images. This is done by highlighting the patterns within images. Here are the pros, cons, and price of Google DeepDream.

  • Pros

Customizable Parameters: Users can easily change settings as per their artistic style.

Creative Output: It fluently generates visually striking and unique images.

Open-Source: It is free and is supported by a huge community.

  • Cons

Technical Setup: It requires high technical expertise to be used effectively.

Niche Focus: It's primarily beneficial for creative and artistic applications.

Resource Intensive: It demands major computational power.

  • Pricing

Free

DALL-E 2

DALL-E 2, developed by OpenAI, is a generative model. It is popular for creating high-quality images as per the inserted textual descriptions. This has enabled production of creative and detailed visual outputs. Here are the pros, cons, and price of DALL-E 2.

  • Pros

Innovative Applications: It is useful for design, creative content generation and marketing.

High-Quality Images: It produces imaginative and detailed images.

API Access: It is easy to integrate into multiple applications.

  • Cons

Ethical Issues: It can be misused in creating inappropriate or deepfakes content.

Access Restrictions: It may also require approval or have waitlists for access.

Cost: Can prove to be expensive for extensive use.

  • Pricing

Pay-per-use. Approx. $0.10 per image generation.

Artbreeder

Artbreeder is a popular collaborative platform. It employs generative adversarial networks (GANs) for creating and modifying images via a blend of user inputs. Here are the pros, cons, and price of Artbreeder.

  • Pros

High Customization: It has a wide range of parameters and styles to adjust.

Interactive & Collaborative: Users can easily blend images and share their creations.

Creative Community: It engages a wide user base for collaboration and inspiration.

  • Cons

Input Dependent: Its results vary as per the quality of the input.

Limited to Images: It primarily focuses on image creation.

Subscription Fees: A few of its features require paid subscriptions.

  • Pricing

Free trial available. Premium plans commence at $8.99/ month.

AIVA (Artificial Intelligence Virtual Artist)

AIVA or Artification Intelligence Virtual Artist is an AI-powered music composition tool. It composes original music tracks for multiple uses. These could be commercials, games and even films. Here are the pros, cons, and price of AIVA.

  • Pros

Ease of Use: It has a super user-friendly interface that promotes quick composition.

Versatile Music Creation: It generates music in different genres and styles.

Licensing Options: It is apt for commercial use when done with proper licensing.

  • Cons

Creative Limitations: It often lacks the nuance and depth of human-composed music.

Subscription Costs: Its higher pricing tiers for commercial use makes it a heavy investment.

Service Dependence: It relies greatly on ongoing updates and support.

  • Pricing

Free plan available. Premium subscriptions commence at $15/ month.

Related Article- History Of Generative AI

How Can Businesses Use Generative AI Tools?

Businesses can utilize generative AI tools for enhancing efficiency, creating personalized customer experiences and driving innovation across different domains. Here is how businesses utilize these tools.

Content Creation

  • Marketing & Advertising: These tools help in automating high-quality marketing material generation. This includes social media posts, email campaigns and advertisements. All of these are tailored to target audiences.
  • Blogging & Copywriting: They produce engaging articles, product descriptions and blog posts. This reduces the effort and time required for content creation.

Entertainment and Media

They help create music, video content and scripts. This enables highly efficient production processes throughout the entertainment industry.

Customer Interaction

  • Chatbots & Virtual Assistants: They improve customer service as AI-driven chatbots are deployed. These offer accurate and instant responses to customer inquiries. All this leads to enhanced satisfaction and reduced support costs.
  • Personalized Recommendations: AI tools generate customized offers and product recommendations as per the customer behavior and preferences. It leads to increased sales and customer loyalty.

Design and Creativity

  • Product Design: They facilitate generation of new product designs, packaging concepts and prototypes quickly. It all enables rapid innovation and iteration.
  • Visual Arts: They create unique logos, visual content and graphics for better branding and promotional materials.

Research and Development

  • Data Augmentation: These tools produce synthetic data that helps in augmenting datasets. These datasets are then used to train ML models and improve model accuracy without any compromise on data privacy.
  • Drug Discovery: These accelerate the process of drug discovery. This is achieved by generating potential compounds as well as simulating their interactions. It all leads to reduced costs and time in pharmaceutical research.

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