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OpenAI and Microsoft implement Vall-E: the new voice chatbot that expands the power of artificial intelligence
14 Feb 2023
February 19, 2023
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OpenAI and Microsoft continue the battle with Google in artificial intelligence by implementing Vall-E, the new voice chatbot. This is a speech synthesis software that can simulate the human voice after just three seconds of listening.

In other words, this is the latest piece of the generative artificial intelligence system developed by Microsoft and OpenAI, with which since 2019 the colossus of Bill Gates is linked by a multi-year, multibillion-dollar partnership.

Vall-E: all the details about the new chatbot from OpenAI and Microsoft

Valle-E is a tool of AGIArtificial General Intelligence, that is, a “general” or “strong” artificial intelligence that can simulate human intelligence. Thus, as opposed to what we have known so far, which is “narrow” or “weak” AI.

The latter is able to respond with preset actions to specific tasks, but not to react to an unplanned action. In recent years, AI chatbots have not performed as well as its creators expected because they were limited to small tasks and had a high error rate.

Valle-E was developed to be used with high-quality speech synthesis tools and to create original audio from an example sample. OpenAI defines Valle-E as a “natural codec language model,” as its operation is based on a technology called EnCodec.

The startup, funded by Elon Musk and Sam Altman, among others, also boasts the creation of ChatGPT, a chatbot that can sustain an interactive conversation with users by remembering and learning from previous actions and precedents.

Hence, just as ChatGPT is able to generate codes autonomously, Valle-E is also designed to create discrete audio codecs from listening to an audio sample.

Behaving precisely as a human.

Together with the GPT-3 software for text and Dall-E/Stable Diffusion for images, the Valle-E audio system completes the ChatGPT triptych and aims to revolutionize the field of generative AI.

Speaker Prompt, Ground Truth, Baseline and Vall-E.

The sophistication of the new tool launched by OpenAI and Microsoft lies in Valle-E’s ability to recognize the timbre, inflection, and emotional tone of the person who is speaking and replay it after only three seconds of listening.

The applications in audio editing are many, as are the criticisms of the software’s potential for manipulation and misuse. Not surprisingly, unlike what happened with ChatGPT, Microsoft did not provide the code for Vall-E for others to experiment with.

Samples of speech already synthesized by the software can also be found on the Valle-E site. In particular, several sampling variants can be heard including: Speaker Prompt, Ground Truth, Baseline, and Vall-E

The first option is an audio clip whose speech connotations have to be reproduced by the AI; in the second, a sentence is spoken for which the AI has to propose a comparison. The third, on the other hand, is an example generated with currently available speech synthesis technologies. Finally, Vall-E is the original speech generated by Microsoft’s software.

Potentialities and dangers of OpenAI and Microsoft’s AI.

Microsoft and OpenAI researchers seem aware of the potential harms of this technology. In fact, they communicated in a public paper the following:

“Since Vall-E could synthesize speech that maintains the identity of the speaker, such technology could pose potential risks related to improper use of the model, such as spoofing voice identification or impersonating someone.”

Therefore, Microsoft adds, to mitigate such risks, a detection model can be built to distinguish whether an audio clip has been synthesized by Vall-E. In this regard, the two giants will also implement Microsoft’s artificial intelligence principles during further model development.

However, the risk of emulation is not the only factor generating skepticism and fear. Vall-E was trained using the LibriLight audio library made by Meta, which contains 60 thousand hours of English-language speeches extracted mostly from public domain audiobooks, recorded and read by volunteers.

In any case, to increase its synthesis capacity, Vall-E will need to expand its learning pool to the entire Internet. This next step is what enabled GPT-3, ChatGPT’s predecessor, to achieve impressive sentence processing, writing, and assembly capabilities.

Despite this, the software was also prone to formulating violent, sexist and racist content precisely because it worked on examples taken indiscriminately from the entire Web. This is what could also happen with the new Vall-E.

In this case, filtering operations would require the use of numerous human staff, which, at the moment, the big digital giants do not seem to foresee given the wave of layoffs that is affecting big tech.

Google unveils Bard to compete with OpenAI and Microsoft

As anticipated, competing with Microsoft and OpenAI is Google, which is set to unveil Bard, the chatbot from DeepMind, the company acquired by Google’s Alphabet. Bard looks like an exact copy of ChatGPT, but without the flaw in updates.

Sundar Pichai, Google’s CEO, presented the new software as a tool that draws information from the web to provide fresh, high-quality responses. By “fresh,” he means continuously updated, something Microsoft’s AI still fails to do.

In a nutshell, Bard aims to generate detailed answers to simple questions. Its operation is based on LaMDA, the Language Model for Dialogue Applications, which one of Google’s own engineers had previously described as “sentient.”

There is no denying that Google’s announcement of Bard’s launch was expected by technology enthusiasts. After all, according to reports in the Wall Street Journal, Alphabet, Google’s parent company, has invested more than $31 billion in artificial intelligence in 2021, more than any other competitor.

After the success of ChatGPT, the company therefore decided to summon the very best: founders Larry Page and Sergey Brin. In any case, there is no doubt that artificial intelligence software is an invaluable resource in the field of innovation.

Indeed, even Amazon, Meta, and Apple are certainly not going to sit back and watch what others are doing without taking action. However, while competition is a great accelerator in terms of research, there is a risk that, in the race for the best artificial intelligence, flawed systems with errors, limitations and risks will be used without paying too much attention to the big picture.

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This development is closer to science fiction than traditional finance. The same oracle network, Pyth, that secures data for over 350 decentralized applications (dApps) across more than 50 blockchains, processing over $2.5 trillion in total trading volume through its oracles, is now the system of record for the United States' core economic indicators. Pyth's extensive infrastructure, spanning over 107 blockchains and supporting more than 600 applications, positions it as a trusted source for on-chain data. This is not about speculative assets; it's about leveraging proven, robust technology for critical public services.

The significance of this collaboration cannot be overstated. By bringing official statistics on-chain, the U.S. government is embracing cryptographic verifiability and immutable publication, setting a new precedent for how governments interact with decentralized technology. This initiative aligns with broader transparency goals and is supported by Secretary of Commerce Howard Lutnick, positioning the U.S. as a world leader in finance and blockchain innovation. The decision by a federal entity to trust decentralized oracles with sensitive economic data underscores the growing institutional confidence in these networks.

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US Dept of Commerce to publish GDP data on blockchain

On Tuesday during a televised White House cabinet meeting, Commerce Secretary Howard Lutnick announced the intention to publish GDP statistics on blockchains. Today Chainlink and Pyth said they were selected as the decentralized oracles to distribute the data.

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The data includes Real GDP and the PCE Price Index, which reflects changes in the prices of domestic consumer goods and services. The statistics are released monthly and quarterly. The biggest initial use will likely be by on-chain prediction markets. But as more data comes online, such as broader inflation data or interest rates from the Federal Reserve, it could be used to automate various financial instruments. Apart from using the data in smart contracts, sources of tamperproof data 👉will become increasingly important for generative AI.

While it would be possible to procure the data from third parties, it is always ideal to get it from the source to ensure its accuracy. Getting data directly from government sources makes it tamperproof, provided the original data feed has not been manipulated before it reaches the oracle.

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List Of Cardano Wallets

Well-known and actively maintained wallets supporting the Cardano Blockchain are EternlTyphonVesprYoroiLaceADAliteNuFiDaedalusGeroLodeWalletCoin WalletADAWalletAtomicGem WalletTrust and Exodus.

Note that in case of issues, usually only queries relating to official wallets can be answered in Cardano groups across telegram/forum. You may need to consult with specific wallet support teams for third party wallets.

Tips

  • Its is important to ensure that you're in sole control of your wallet keys, and that the keys used can be restored via alternate wallet providers if a particular one is non-functional. Hence, put extra attention to Non-Custodial and Compatibility fields.
  • The score column below is strictly a count of checks against each feature listed, the impact of specific feature (and thus, score) is up to reader's descretion.
  • The table represents current state on mainnet network, any future roadmap activities are out-of-scope.
  • Info on individual fields can be found towards the end of the page.
  • Any field that shows partial support (eg: open-source field) does not score the point for that field.

Brief info on fields above

  • Non-Custodial: are wallets where payment as well as stake keys are not shared/reused by wallet provider, and funds can be transparently verified on explorer
  • Compatibility: If the wallet mnemonics/keys can easily (for non-technical user) be used outside of specific wallet provider in major other wallets
  • Stake Control: Freedom to elect stake pool for user to delegate to (in user-friendly way)
  • Transparent Support: Easy approachability of a public interactive - eg: discord/telegram - group (with non-anonymous users) who can help out with support. Twitter/Email supports do not count for a check
  • Voting: Ability to participate in Catalyst voting process
  • Hardware Wallet: Integration with atleast Ledger Nano device
  • Native Assets: Ability to view native assets that belong to wallet
  • dApp Integration: Ability to interact with dApps
  • Stability: represents whether there have been large number of users reporting missing tokens/balance due to wallet backend being out of sync
  • Testnets Support: Ability to easily (for end-user) open wallets in atleast one of the cardano testnet networks
  • Custom Backend Support: Ability to elect a custom backend URL for selecting alternate way to submit transactions transactions created on client machines
  • Single/Multi Address Mode: Ability to use/import Single as well as Multiple Address modes for a wallet
  • Mobile App: Availability on atleast one of the popular mobile platforms
  • Desktop (app,extension,web): Ways to open wallet app on desktop PCs
  • Open Source: Whether the complete wallet (all components) are open source and can be run independently.

Source

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XDC: xdcc2C02203C4f91375889d7AfADB09E207Edf809A6

 

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