Big News: Now GPT-4 Time: What is the difference Between ChatGpt-3.5 and GPT-4? Everything you should know:
There are 5 differences between GPT-4 and GPT-3.5:
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Multi-language support
GPT3.5 was based only on English, GPT4 has been trained in 26 languages across the world, including five Indian regional languages like Bangla, Urdu, Punjabi, Marathi, and Telugu.
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GPT-4 has More data and bigger memory
GPT-3.5 is to be based on 175 billion data points as part of its training database
GPT4 is to be based on nearly 3 trillion data points.
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Multi-modal inputs
GPT-3.5 only take text inputs to generate results,
but GPT4 will also allow users to submit images as part of their queries.
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GPT4 has greater reasoning and accuracy
GPT-4 that the larger amounts of data and memory have made the new LLM better at reasoning
and 40% more likely to produce factual responses than GPT-3.5.
GPT4 can now also take longer inputs.
Greater reasoning and accuracy are essential traits that canbe achieved through various means such as education, training, practice, and experience. These traits can help individuals make better decisions, solve problems more effectivelyand achieve their goals more efficiently.
It is important to note that more significant reasoning and accuracy are essential for individual success andthe greater good of society. Individuals can contribute to a more informed, and productive community by making better decisions and producing more accurate information.
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GPT4 has better safety protocols and steerability
Openai GPT4 maybe offer better safety protocols for a safer chatbot.
Secure technology can be achieved through various measures such as encryption, multi-factor authentication, firewalls, antivirussoftware, intrusion detection systems, and regular software updates. It is important to note that no technology can be completely secure, but implementing these measures can significantly reduce therisk of a security breach.
Multi-language support technology refers to software or systems that can operate in multiple languages and accommodate users who speak different languages. With the rise of globalization and the internet, multi-language support has become increasingly essential to meet the needs of a diverse population.
There are different ways that multi-language support technology can be implemented. Some examples include:
Multilingual user interfaces: Software or applications that offer user interfaces in different languages, allowing users to switch between languages depending on their preferences.
Machine translation: Software that can translate text or speech from one language to another. While machine translation is imperfectit can be helpful for essential communication and understanding.
Localization: Adapting software or content to a specific language or culture. This can include adapting language, currency, date formats, and other elements to match local conventions.
Speech recognition: Technology that can recognize speech in different languages, allowing users to interact with devices using their voice.
Multi-language support technology can be instrumental in business, e-commerce, and customer service, where it can help companies reach a broader audienceand provide better service to their customers. It can also be important in healthcare, education and government, facilitating communication between individuals who speak different languages.
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