Research & Developement
A user-friendly AI search engine with ChatGPT integration.
GPTGO is a brilliant AI search engine that combines the power of Google search with ChatGPT, making your search experience way more enjoyable.
It’s so easy to use GPTGO, you don’t need to set up a GPTGO account, you can use it on any web browser AND it’s totally free to use - hallelujah! You just need to include your query in the search bar, press ‘Ask GPT’ or ‘Search & Ask GPT’ and in a matter of seconds you’ll have results. Sharing answers from Google alongside a response from Chat GPT. It’s great to have both results side by side. Dig into the Google links or ask ChatGPT more questions, it’s as simple as that.
Another great thing about GPTGO is that it supports many different languages, making it accessible to all. If you’re worried from a security point of view, no need! GPTGO does not store or track any of your information, so you’re safe and sound when searching. If you find yourself wanting to search on the go, GPTGO also has a mobile app called GO AI which is available on both iOS and Android (FYI, you can only download this directly from the GPTGO site).
Now, if that wasn’t enough, GPTGO also has a great Discord server that you can get involved in. With over 4,000 members you can discuss your findings, ask questions, or simply make new friends. You can even request new features through the Discord server or flag any bugs you come across. If you want to learn more about AI itself, there’s a great blog section that has a wide range of articles on everything AI-related, so you can stay up to date, keep your knowledge tip-top, and learn something new.
If you want to try something new when it comes to your search engine, why not mix it up and give GPTGO a go. It’s free! You’d be silly not to give it a GPTGO.
Features
- AI search engine
- Universal device compatibility
- ChatGPT integration
- Search result enhancements
Use Cases
- It does rely on AI, so remember results may not always be 100% accurate.
Best for
The AllThingsAI Verdict
You can use GPTGO without any worry. I really like that you don’t have to create an account to use this search engine. You can use it as much as you want without any commitment, it’s great. I think the integration with ChatGPT is a brilliant idea, it allows you to dig deeper into the results, ask questions and find what you’re hunting for, a lot quicker.
GPTGO is a really nice search engine alternative. It’s super simple, has an easy-to-use interface and you’re getting double the information - what’s not to like!
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Valence Discovery uses AI-enabled drug design tools to help scientists design new drugs faster and easier.
Valence Discovery uses AI-enabled drug design tools to help scientists design new drugs faster and easier.
Valence Discovery is an AI-enabled drug design software that provides drug discovery scientists with the latest advances in AI-enabled drug design capabilities. It offers a comprehensive suite of tools to help scientists design new drugs quickly and easily, while providing a user-friendly interface.
According to the website, the software stands out from its competitors by offering a unique approach to drug design tailored to the needs of drug discovery scientists. Its features enable pharmaceutical researchers to leverage AI-enabled drug design to identify and develop new drugs faster, medical professionals to stay up-to-date with the latest advances in drug design, and drug manufacturers to identify potential drug targets and design drugs efficiently.
Features
- Valence Discovery provides AI-enabled drug design to empower drug discovery scientists.
- The software offers the latest advances in AI research for drug discovery.
- The platform provides a comprehensive suite of tools to help scientists design new drugs.
- Valence Discovery offers a unique approach to drug design that is tailored to the needs of drug discovery scientists.
- The software provides a user-friendly interface to help scientists quickly and easily design new drugs.
Use Cases
- Pharmaceutical researchers can use Valence Discovery to leverage AI-enabled drug design to identify and develop new drugs faster.
- Medical professionals can use Valence Discovery to stay up-to-date with the latest advances in drug design, helping them to make informed decisions about prescribing medication.
- Drug manufacturers can use Valence Discovery to identify potential drug targets and design drugs more efficiently, allowing them to bring new drugs to market faster.
Best for
- Valence Discovery provides drug discovery scientists with the latest AI-enabled drug design capabilities.
- The software offers a comprehensive suite of tools to help scientists design new drugs quickly and easily.
- The platform features a user-friendly interface to enable drug discovery scientists to utilize the latest advances in AI research.
The AllThingsAI Verdict
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Splitter is an AI audio processing solution that quickly and accurately separates instruments from music, ideal for music producers, sound engineers, and DJs.
Splitter is an AI audio processing solution that quickly and accurately separates instruments from music, ideal for music producers, sound engineers, and DJs.
Splitter is an AI audio processing company used by millions of people around the world. According to the website, its services include stem separation from music, allowing users to isolate instruments from music and it is based on Deezer's open source research project Spleeter. This makes it a reliable and efficient way to process audio with AI. Splitter offers both free and paid services and is ideal for music producers, sound engineers and DJs who need to quickly and accurately process audio with AI. It differentiates itself from similar software competitors by offering free and paid services and being based on Deezer's open source research project Spleeter.
Features
- Splitter offers AI audio processing services for millions of users worldwide.
- Its services include stem separation from music, allowing users to isolate instruments from music.
- It is based on Deezer's open source research project Spleeter.
- It offers both free and paid services.
- It is a reliable and efficient way to process audio with AI.
Use Cases
- Music producers can use Splitter to isolate individual instruments from a track, allowing them to mix and master with greater precision.
- Sound engineers can use Splitter to quickly separate audio stems from a track, allowing them to quickly and accurately adjust the levels of each instrument.
- DJs can use Splitter to quickly isolate the vocals from a track, allowing them to create unique remixes and mashups.
Best for
- Splitter is an ideal tool for isolating instruments from music, allowing users to separate individual sounds from a track.
- Using Splitter, users can quickly and accurately process audio with AI, providing reliable and efficient results.
- Splitter is based on Deezer's open source research project Spleeter, providing users with access to cutting-edge AI audio processing services.
The AllThingsAI Verdict
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Cradle helps biologists design improved proteins faster and more efficiently with powerful algorithms, AI suggestions, and bank-grade security.
Cradle helps biologists design improved proteins faster and more efficiently with powerful algorithms, AI suggestions, and bank-grade security.
Cradle is a software that helps biologists design improved proteins faster and more efficiently. It features powerful prediction algorithms and AI design suggestions, such as AlphaFold 2, to optimize the thermostability of proteins and optimize codons for better expression.
Biologists, software engineers, and researchers can also use Cradle to generate quality candidates in just one click, and optimize multiple phenotypes simultaneously to find an optimum.
Cradle also has bank-grade level security to keep data safe. This software differentiates itself from competitors by providing a one-click feature to generate quality protein candidates, as well as the ability to optimize multiple phenotypes simultaneously to find an optimum.
Features
- Generate quality protein candidates with just one click.
- Leverage machine learning models to optimize codons for better expression.
- Set targets for multiple phenotypes simultaneously and let the models find an optimum.
- Utilize bank-grade security to keep data safe.
- Access sequence data only with permission from the organization.
Use Cases
- Biologists can use Cradle to design improved proteins in record time using powerful prediction algorithms and AI design suggestions, such as AlphaFold 2, to optimize the thermostability of proteins and optimize codons for better expression.
- Software engineers can use Cradle to build tailored models that improve candidates with each round of testing, as well as use bank-grade level security to keep data safe.
- Researchers can use Cradle to generate quality candidates in just one click, and optimize multiple phenotypes simultaneously to find an optimum.
Best for
- Generate high-quality protein candidates quickly and efficiently with Cradle's one-click feature.
- Optimize codons for better expression with Cradle's machine learning models.
- Ensure data security with Cradle's bank-grade security measures.
The AllThingsAI Verdict
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CarperAI helps developers and data scientists gain insights into customer preferences and better understand code changes with AI-trained models and datasets.
CarperAI helps developers and data scientists gain insights into customer preferences and better understand code changes with AI-trained models and datasets.
CarperAI is a democratized AI research team that enhances the performance of preference learning. It offers a CARP model that produces embeddings of passages and reviews with high similarity, as well as a CARP-CoOp model that uses context optimization to tune reviews. The team also offers diff models trained on millions of commits scraped from GitHub. According to the website, these models help developers better understand code changes and data scientists gain insights into customer preferences. CarperAI differentiates itself from competitors by offering a Story-Critique dataset that provides an information-rich measure of preferences on story content.
Features
- CARP model produces embeddings of passages and reviews, where high similarity between passages and review embeddings generally corresponds to reviews that fit the given passage.
- CARP-CoOp uses context optimization to tune reviews before feeding them to CARP's review encoder.
- The company releases a series of diff models, trained to predict a code diff, trained on millions of commits scraped from GitHub.
- The team has interests in learning theory, natural language preference learning and their combinations.
- The team is interested in the future of code, art, and machine learning.
Use Cases
- Software developers can use CarperAI's diff models to predict code diffs, helping them to better understand the changes made to their code.
- Data scientists can use CarperAI's Story-Critique dataset to gain insights into the preferences of their customers.
- AI researchers can use CarperAI's CARP model to measure how well a story does under a certain preference.
Best for
- CarperAI's CARP model can generate embeddings of passages and reviews, providing a measure of how well a review fits a story.
- The CARP-CoOp model uses context optimization to tune the review before feeding it to CARP's review encoder, enabling it to measure how well a story meets a specified preference.
- CarperAI's diff models are trained to predict a code diff, trained on millions of commits scraped from GitHub, making them ideal for analyzing large amounts of code.
The AllThingsAI Verdict
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