The Most Popular AI Platforms in 2024
Some of the most beloved AI platforms covering various AI application areas by 2024 are as follows.
Platforms for General AI:
1. AI powered by Microsoft Azure:
A whole range of products and services for building, maintaining and deploying large-scale AI instances in the cloud. Acting as another window is Microsoft techcommunity.com
2. Azure AI platform from Microsoft:
Google Cloud AI: Offers a selection of tools on Google’s cloud infrastructure for computer vision, natural language processing, machine learning, and other applications. Functions as a new window Linkedin.com
3. Platform AI on Google Cloud :
Machine learning models can be created, trained, and deployed on Amazon Web Services using the cloud-based tool Amazon Sage Maker. Medium.com opens in a new window. AI chat bots on the Amazon Sage Maker platform.
4. The Chat GPT App :
Jasper is an AI writing assistant that assists in producing blog entries, social media content, and marketing copy. Functions as a new window Zippier Jasper, an artificial intelligence writing assistance.
Artificial Intelligence Image Producer:
1. Mid-journey:
Constructs creative, high-quality graphics from written descriptions. Functions as a new window arstechnica.com
2. Mid-Journey AI image generator DALL-E 3:
Produces imaginative and realistic visuals in response to textual cues. Functions as a new window at uxplanet.org
3. AI image generator Dalle 3 :
Dream Studio:
Creates artwork and photo realistic visuals with text descriptions. Functions as a new window neural networkpress.com . The AI image creator in Dream Studio.
Additional Platforms with Specialization:
1. Tensor Flow:
Data flow graphs are used in numerical computations with this open-source machine learning package. Py Torch is an open-source machine learning package used for deep learning model construction and training.
2. On-premise vs. cloud:
On-premise systems give greater control and protection, but cloud platforms are more salable and user-friendly.
3. Usability:
While some platforms have more intuitive user interfaces, others demand programming experience.
4. IBM Watson:
IBM Watson offers enterprises AI-powered solutions in the areas of data analytics, computer vision, and natural language comprehension. It provides tools like Watson Studio for data scientists and Watson Assistant for creating chatbots.
5. Salesforce Einstein:
Salesforce uses Einstein AI, which offers capabilities including automated insights, natural language processing, and predictive analytic, to incorporate AI into its customer relationship management (CRM) platform.
6. Facebook AI:
The division dedicated to researching artificial intelligence at Facebook works to advance the field, develop AI technologies that are integrated into Facebook products, and contribute to a number of open-source projects. Of course! Other well-known AI systems that are gaining popularity across a range of industries are as follows:
7. NVIDIA Deep Learning AI:
For deep learning and artificial intelligence applications, NVIDIA offers hardware and software solutions. These systems have been shown to significantly enhance efficiency and accuracy in various tasks.
8. Intel AI:
Intel provides a variety of AI hardware and software solutions, such as frameworks like the Intel Distribution of Open VINO Toolkit for deploying deep learning models at the edge, AI development tools, and CPUs designed for AI workloads.
9. Baidu AI:
Renowned for its AI research and development, Baidu is a prominent Chinese technology business. Baidu’s artificial intelligence platform consists of services including Apollo, an open-source autonomous driving system; Due OS, a conversational AI platform; and Baidu Brain, its AI technology platform.
10. Ten-cent AI:
Via its cloud services platform, Ten-cent, a significant Chinese tech corporation, provides AI technologies. Ten-cent’s AI technologies, which enable applications in the gaming, social media, and finance industries, include speech recognition, computer vision, and natural language comprehension.
11. Huawei AI:
With its cloud and device ecosystems, Huawei offers AI solutions. Their AI platform supports sectors including telecommute, smart cities, and healthcare by encompassing topics like intelligent computing, AI chips, and develop tools.
12. Apple Core ML:
Applications for iOS, ma Cos, watch OS, and tv OS can use machine learning models thanks to Apple’s Core ML framework. By enabling on-device inference, it protects user privacy and lessens the need for cloud services to process AI.
By User Population:
1. General Purpose:
Fiver (AI micro tasks such as data annotation); Up-work (links independent contractors with AI development projects);
2. Enterprise-focused:
Google Cloud AI Platform, Microsoft Azure AI, and Amazon Sage Maker (serving huge enterprises with intricate AI requirements) Tensor Flow and Py Torch are popular tools used by academics and researchers for experimentation and prototyping in research and development.
By Price:
1. Open-Source:
PyTorch, Keras, Tensor Flow (free to use and modify). Cloud-based pricing methods that are based on resource utilization include Amazon Sage Maker, Google Cloud AI Platform, and Microsoft Azure AI.
2. Based on Subscription:
Certain specialized AI platforms may charge a subscription fee in order to use their services or tools.
3. By Usability:
Keras (a high-level API with an intuitive user interface) is beginner-friendly. Tensor Flow and PyTorch are intermediate users (need some programming skills)
4. Advanced Users:
To fully utilize the potential of all platforms, a high level of machine learning, artificial neural network, and deep learning algorithm experience is necessary. These platforms can be used for sophisticated AI projects.