


Worried about being stuck due to overreliance on OpenAI, software developers are looking for alternative technologies.
As AIGC becomes increasingly popular, some people predict that the AI market will grow several times in the next few years, and the market size is expected to reach US$90 billion by 2025. But OpenAI may not be the only player that can claim this big pie.
News on March 30, the AIGC craze started by ChatGPT has detonated the world, and almost every industry is reflecting on how to use it. However, some software developers are looking for alternative technologies due to concerns about over-reliance on OpenAI, which first launched the technology.
As AIGC becomes increasingly popular, some predict that the AI market will grow several times in the next few years, and the market size is expected to reach US$90 billion by 2025. But OpenAI may not be the only player that can claim this big pie.
According to foreign media reports, more than a dozen startups and investors said they are looking to Turning to competitors of industry leader OpenAI casts a pall over Microsoft and OpenAI's ambitions to dominate the emerging field.
AI investor George Mathew compared the basic model of AI to other technological breakthroughs that have spawned competition. Matthew said: "Do we only have one Internet service provider? Of course not, so we will also need multiple AI basic model providers to build an ecosystem that can operate more healthily. OpenAI is just a first step at the moment, but it will not Becoming our only option."
AI storytelling startup Tome helps users build slideshows faster, with its system originally built on GPT-3, which OpenAI first released in 2020 AI basic model. Tome said the company has reached 3 million users this month and has begun experimenting with other AI models.
Tome has introduced the text model of OpenAI competitor Anthropic and plans to switch from OpenAI’s photo generation model Dall-E to Stable Diffusion, an open source model developed by Stability AI. "Our goal is to find the best model for each task with the least latency and the best quality," said Tome CEO Keith Peiris.
AI software developers and investors According to the reporter, in order to provide more reliable services, control costs, and utilize the professional knowledge of different models, reducing reliance on a single model has become a new consensus in the industry.
OpenAI became a household name after chatbot ChatGPT shocked many with its ability to answer complex questions with clarity, grammatical correctness, and a human-like appearance. It has attracted more than $10 billion in investment from Microsoft, while rivals including Google and other smaller companies are scrambling to create new AI models.
By any measure, OpenAI’s new GPT-4 model is still the most powerful. Estimates released by PitchBook, a global data research organization, show that the AIGC market size is expected to grow to US$98.1 billion by 2026.
As the infrastructure layer of AI applications, the basic model has attracted the most investment from venture capitalists and strategic investors. For companies like OpenAI, how these basic models are used is crucial. OpenAI has said it hopes to achieve $1 billion in revenue by 2024, and the company expects revenue to reach $200 million this year.
As a way to make money, OpenAI charges $0.06 for processing 1,000 token tips in the latest GPT-4 model and has launched a ChatGPT subscription service that charges users $20 per month.
Startups are also concerned that Microsoft could compete with its AI customers as the tech giant integrates OpenAI models into products ranging from search to office suites.
Mike Volpi, a partner at Index Ventures, which backs OpenAI competitor Cohere, said: "Many of these products may use sensitive company data, and the underlying models will see the relationship between these companies and their own customers. Interaction. Many of these companies will not feel comfortable relying on Microsoft or a company that is generally controlled by Microsoft."
Both OpenAI and Microsoft declined to comment.
Dave Rogenmoser, CEO of AI copywriting platform Jasper, admitted that the company’s writing assistant Jasper.ai was originally built using OpenAI models, but it did not want to rely on a single model . To that end, Jasper adds Cohere and Anthropic, two other large language modeling companies that have cloud computing partnerships with Google and are launching their own AI engines to help marketers tailor voices through the use of hybrid models.
Matt Shumer, CEO of HyperWite, another AI copywriting app, said the app matches each user’s actions with different models based on various considerations. For example, it uses OpenAI's model to generate long articles and uses the Coherence model to automatically complete sentences faster and at a lower cost.
Others are looking for alternatives simply because OpenAI is struggling to keep up with growing demand. Srinath Sridhar, CEO of Regie.ai, a writing assistant who serves the sales team, said: "OpenAI's server crashed. We want users to have a better experience while using more This model helps us process queries at a lower cost.”
To be sure, many startups, including customer service software company Intercom, are still betting all on OpenAI. Fergal Reid, the company's head of machine learning, admitted that OpenAI's use of GPT-4 is "very expensive." But he added: "We currently believe we need to use GPT-4 in order to get the accuracy we need to best serve our customers."
The above is the detailed content of Worried about being stuck due to overreliance on OpenAI, software developers are looking for alternative technologies.. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











DMA in C refers to DirectMemoryAccess, a direct memory access technology, allowing hardware devices to directly transmit data to memory without CPU intervention. 1) DMA operation is highly dependent on hardware devices and drivers, and the implementation method varies from system to system. 2) Direct access to memory may bring security risks, and the correctness and security of the code must be ensured. 3) DMA can improve performance, but improper use may lead to degradation of system performance. Through practice and learning, we can master the skills of using DMA and maximize its effectiveness in scenarios such as high-speed data transmission and real-time signal processing.

Using the chrono library in C can allow you to control time and time intervals more accurately. Let's explore the charm of this library. C's chrono library is part of the standard library, which provides a modern way to deal with time and time intervals. For programmers who have suffered from time.h and ctime, chrono is undoubtedly a boon. It not only improves the readability and maintainability of the code, but also provides higher accuracy and flexibility. Let's start with the basics. The chrono library mainly includes the following key components: std::chrono::system_clock: represents the system clock, used to obtain the current time. std::chron

The built-in quantization tools on the exchange include: 1. Binance: Provides Binance Futures quantitative module, low handling fees, and supports AI-assisted transactions. 2. OKX (Ouyi): Supports multi-account management and intelligent order routing, and provides institutional-level risk control. The independent quantitative strategy platforms include: 3. 3Commas: drag-and-drop strategy generator, suitable for multi-platform hedging arbitrage. 4. Quadency: Professional-level algorithm strategy library, supporting customized risk thresholds. 5. Pionex: Built-in 16 preset strategy, low transaction fee. Vertical domain tools include: 6. Cryptohopper: cloud-based quantitative platform, supporting 150 technical indicators. 7. Bitsgap:

Handling high DPI display in C can be achieved through the following steps: 1) Understand DPI and scaling, use the operating system API to obtain DPI information and adjust the graphics output; 2) Handle cross-platform compatibility, use cross-platform graphics libraries such as SDL or Qt; 3) Perform performance optimization, improve performance through cache, hardware acceleration, and dynamic adjustment of the details level; 4) Solve common problems, such as blurred text and interface elements are too small, and solve by correctly applying DPI scaling.

C performs well in real-time operating system (RTOS) programming, providing efficient execution efficiency and precise time management. 1) C Meet the needs of RTOS through direct operation of hardware resources and efficient memory management. 2) Using object-oriented features, C can design a flexible task scheduling system. 3) C supports efficient interrupt processing, but dynamic memory allocation and exception processing must be avoided to ensure real-time. 4) Template programming and inline functions help in performance optimization. 5) In practical applications, C can be used to implement an efficient logging system.

The main steps and precautions for using string streams in C are as follows: 1. Create an output string stream and convert data, such as converting integers into strings. 2. Apply to serialization of complex data structures, such as converting vector into strings. 3. Pay attention to performance issues and avoid frequent use of string streams when processing large amounts of data. You can consider using the append method of std::string. 4. Pay attention to memory management and avoid frequent creation and destruction of string stream objects. You can reuse or use std::stringstream.

Measuring thread performance in C can use the timing tools, performance analysis tools, and custom timers in the standard library. 1. Use the library to measure execution time. 2. Use gprof for performance analysis. The steps include adding the -pg option during compilation, running the program to generate a gmon.out file, and generating a performance report. 3. Use Valgrind's Callgrind module to perform more detailed analysis. The steps include running the program to generate the callgrind.out file and viewing the results using kcachegrind. 4. Custom timers can flexibly measure the execution time of a specific code segment. These methods help to fully understand thread performance and optimize code.

Efficient methods for batch inserting data in MySQL include: 1. Using INSERTINTO...VALUES syntax, 2. Using LOADDATAINFILE command, 3. Using transaction processing, 4. Adjust batch size, 5. Disable indexing, 6. Using INSERTIGNORE or INSERT...ONDUPLICATEKEYUPDATE, these methods can significantly improve database operation efficiency.
