Archive for Redaccion

The Latest on AI: GPT-5 Could Achieve AGI by Year’s End The launch of GPT-4 has only just happened, but the buzz surrounding the next version of AI chatbot technology is already growing. The latest claim is that GPT-5 will complete its training this year, with the potential to revolutionize AI. What is AGI and What Could It Mean for AI? According to developer Siqi Chen, GPT-5 is set to complete training in December 2023, with OpenAI hoping to achieve AGI (artificial general intelligence). AGI would allow an AI to understand and learn any task or concept that humans can comprehend. This capability would enable AI to be indistinguishable from humans in terms of its abilities. Positive and Negative Consequences of Achieving AGI The prospect of AGI is significant, as it could lead to increased productivity across various AI-enabled processes, speeding up work and eliminating tedious tasks. However, the potential unintended consequences of granting an AI so much power raises concerns, as the negative effects of AGI are unknown. Timing of GPT-5’s Development OpenAI has predicted that GPT-4.5 will be introduced in September or October 2023 as an intermediate version between GPT-4 and GPT-5. If AGI goes awry, it could enable the spread of incredibly convincing bots on social media, disseminating harmful disinformation and propaganda that is challenging to detect. Elon Musk’s Concerns About AI Bots Elon Musk has been vocal about his concerns, and his tenure as Twitter CEO has focused on fighting AI bots. However, his latest idea of restricting the reach of accounts that have not paid for a Twitter Blue membership has been met with criticism. The Potential Impact of GPT-5 Achieving AGI The AI-enabled future has the potential to transform the way we live, and GPT-5 achieving AGI would be ground-shaking. Whether it will lead to positive or negative consequences is yet to be determined.

Personalization and Spotify Spotify has always been known for its personalized music experiences, from Discover Weekly to Wrapped campaigns. Now, the company is taking personalization to a whole new level with its latest feature, DJ. This personalized AI guide knows you and your music taste so well that it can choose what to play for you. Introducing the AI DJ The DJ feature is designed to deliver a curated lineup of music alongside commentary around the tracks and artists that Spotify thinks you’ll like. It sorts through the latest music and looks back at some of your old favorites, even resurfacing that song you haven’t listened to for years. It then reviews what you might enjoy and delivers a stream of songs picked just for you. And what’s more, it constantly refreshes the lineup based on your feedback. How AI DJ works To create the DJ, Spotify reimagined the way users listen on its platform. The DJ combines Spotify’s personalization technology, which gives you a lineup of music recommendations based on what you like, with generative AI through the use of OpenAI technology. This powerful combination allows the AI to scan the latest releases and provide insightful facts about the music, artists, or genres you’re listening to. The role of generative AI in creating the DJ Spotify’s editors, who are experts in genres and know music and culture inside and out, use this generative AI tooling to scale their innate knowledge in ways never before possible. And with a dynamic AI voice platform from Spotify’s Sonantic acquisition, the DJ brings to life stunningly realistic voices from text. Creating the DJ’s voice model with Xavier “X” Jernigan To create the voice model for the DJ, Spotify partnered with its Head of Cultural Partnerships, Xavier “X” Jernigan. His personality and voice resonated with Spotify’s listeners and resulted in a loyal following for the podcast. His voice is the first model for the DJ, and the company will continue to iterate and innovate, as it does with all its products. Learning and becoming better The DJ feature is currently rolling out in beta, and the more you listen and tell the DJ what you like (and don’t like!), the better its recommendations get. Think of it as the very best of Spotify’s personalization, but as an AI DJ in your pocket. If you’re not feeling the vibe, just tap the DJ button, and it will switch it up. The power of Spotify’s personalization technology In conclusion, Spotify’s new DJ feature is set to take personalized music experiences to a whole new level. By combining Spotify’s personalization technology with generative AI and a dynamic AI voice platform, the DJ can deliver a curated lineup of music alongside commentary around the tracks and artists that Spotify thinks you’ll like. As the more you listen and provide feedback, the better its recommendations get. The DJ is currently rolling out in beta, and users can expect to have their own personalized AI guide in their pockets very soon.

The Current Discourse on Artists vs. Machines Artificial Intelligence (AI) and human creativity may seem like a dichotomy, but in reality, these two can complement each other. Musicians, in particular, have shown an interest in exploring how AI and humans can collaborate rather than compete. Last November, at the Stockholm University of the Arts, an AI and a human made music together. The performance began with musician David Dolan playing the piano into a microphone while the computer system, designed and supervised by composer Oded Ben-Tal, “listened” to the piece and added its accompaniment, improvising like a person would. While the artists-vs-machines discourse about AI replacing journalists or stealing from illustrators continues, musicians are exploring ways to use these models to supplement human creativity. The Historical Speculation on AI and Music For Ben-Tal, creativity includes various aspects such as inspiration, innovation, craft, technique, and graft. He believes there is no reason why computers cannot help in that situation in a way that is helpful. This view is not new, as speculation that computers might compose music has been around as long as the computer itself. Ada Lovelace, a mathematician and writer, once theorized that Charles Babbage’s steam-powered Analytical Engine could be used for more than simply numbers. She believed that the “science of harmony and of musical composition” could be adapted to compose elaborate and scientific pieces of music of any degree of complexity or extent. Musicians’ Reactions to ChatGPT and Bing’s AI Chatbot Artists like Ash Koosha, Arca, and Holly Herndon have already used AI to enrich their music. Holly Herndon’s free-to-use AI-powered vocal clone, Holly+, presented a different side of the narrative around tech and music. She said, “There’s a narrative around a lot of this stuff, that it’s scary dystopian. I’m trying to present another side: This is an opportunity.” Copyright Considerations and Creative Capabilities of AI The use of AI in music raises questions about copyright and whether songwriters can defend themselves against plagiarism or if audiences should be told when AI is used. The Google MusicLM model, which turns text into music, has not been released due to the risks associated with music generation and the potential misappropriation of creative content. However, AI still presents attractive creative capabilities. Musicians can use AI to improvise with a pianist outside of their skill set or draw inspiration from an AI’s compositions in a genre they are not familiar with, like Irish folk music. An Alternative to the Human vs. Machine Narrative While generative AI can be unsettling because it exhibits a kind of creativity normally ascribed to humans, Ben-Tal sees it as another technology, another instrument, in a lineage that goes back to the bone flute. He believes that generative AI isn’t unlike turntables, which allowed artists to scratch records and sample their sounds, creating whole new genres. The Wilder (albeit Controversial) Fantasy of AI Realizing an Artist’s Vision In conclusion, the fear that AI will replace human creativity is unnecessary. AI and humans can collaborate, and their joint efforts could create new genres of music or produce a better version of a composer’s vision. The use of AI in music raises questions about copyright, but it presents attractive creative capabilities in the short and long term. As the artists-vs-machines discourse about AI continues, musicians are quietly exploring how these models might supplement human creativity.

Improved Accuracy and Advanced Reasoning Capabilities On March 14th, 2023, the latest version of the AI software, Chat GPT-4, was launched. Compared to its predecessor, Chat GPT-3, Chat GPT-4 has undergone extensive training on various prompts, including malicious ones, to make it less susceptible to user manipulation. This new version offers more factual and accurate information and has better reasoning capabilities. Multimodal Image Recognition for Real-World Applications Chat GPT-4 is also capable of understanding images, making it multimodal, which means it can understand different modes of information, including words and images. Users can ask the AI to describe an image, making it useful for those with vision difficulties. Additionally, Chat GPT-4 can process up to 25,000 words at once, which is eight times more than Chat GPT-3, making it better equipped to take on larger documents. Increased Processing Power for Efficient Work Environments According to Open AI, Chat GPT-4 outperforms Chat GPT-3 by up to 16% on common machine learning benchmarks, making it more accessible to non-English speakers. Moreover, the latest version is less likely to respond to disallowed content and is 40% more likely to produce factual responses, making it safer to use for users overall. Enhanced Safety Features for User Protection In a comparison between Chat GPT and Chat GPT-4, both AIs were asked the same question, and although both could provide a solution, Chat GPT-4 offered a more accurate and less wordy response, implying it will offer more consistent and fact-based solutions than its predecessor. In conclusion, Chat GPT-4 offers several notable improvements over Chat GPT-3. Its better reasoning capabilities, understanding of images, and ability to process larger documents make it more efficient and versatile. The AI is less susceptible to user manipulation and less likely to respond to disallowed content, making it a safer and more well-rounded experience for users.

A Proof-of-Concept for AlphaFlow’s Efficiency A team of chemical engineering researchers has developed a groundbreaking self-driven lab called AlphaFlow that can optimize the discovery of complex multistep reaction routes for the synthesis of advanced functional materials and molecules. AlphaFlow integrates artificial intelligence (AI) techniques, specifically reinforcement learning, with automated microfluidic devices to accelerate the material discovery process. AlphaFlow’s AI Model and Decision Making Process Traditional techniques for discovering new chemistries rely on varying one parameter at a time, but AlphaFlow can conduct more experiments than 100 human chemists in the same period while using less than 0.01% of the relevant chemicals. The AI model behind AlphaFlow makes decisions on what experiment to conduct next based on data it has developed from experiments it already ran and what it predicts the results of the next several experiments will be. AlphaFlow: Making Discoveries and Optimizations AlphaFlow has a range of applications from discovering new chemicals to optimizing the manufacturing process for known chemicals. For discovery, the system is trying to determine which precursors need to be added, as well as the best order in which to add them, in order to find a chemistry with the best performance. Whereas for optimization, the AI model already knows which precursors need to be added and in which order, and its focus is on determining what amount of each precursor is needed, as well as the amount of time needed for each reaction, to reach optimal performance most efficiently. AI and Chemistry: The Integration That Reduces Development Time AlphaFlow’s integration of AI and chemistry reduces the amount of time it takes to develop new chemistries by at least an order of magnitude. This system also offers new insights into fundamental chemistry by developing a new means of producing a semiconductor nanocrystal with fewer steps, broadening our understanding of the chemistry involved. AlphaFlow and Colloidal Atomic Layer Deposition At present, AlphaFlow is set up to conduct experiments related to colloidal atomic layer deposition, but it could be modified to conduct any range of experiments that involve performing chemical reactions in solution. The researchers are now seeking partners in both the research community and private sector to use AlphaFlow to address chemistry challenges. AlphaFlow: The Future of Chemistry Research? AlphaFlow is open source, and the researchers believe in sharing high-quality, reproducible, standardized, experimental data, both from failures and successes, to accelerate the discovery of new materials and chemical processes. AlphaFlow is the first self-driven lab that integrates reinforcement learning with AI, highlighting the extent to which AI and the physical sciences can benefit each other.

Alethea AI and Polygon Labs are contributing to the AI boom an AI-powered NFT project that will allow users to create NFT avatars through text-based prompts similar to OpenAi’s Dall-E Imager. Faster, more accessible NFT avatar creation The project plans to enable anyone to quickly create, train and exchange AI characters as NFTs in Polygon.” CharacterGPT, developed by Alethea AI, aims to be accessible through traditional text-to-image engines such as Dall-E 2 to go beyond Open AI to generate fully interactive and intelligent AI characters with a one-line natural language message. AI NFT character creation NFTs can be coined in mycharacter.ai through Alethea AI’s Polygon dApp. To launch the app, a digital version of Polygon co-founder Sandeep Nailwal became a 1/1 NFT “AI Collectible that is based on his writings, public statements, and interviews.” The gold mark next to the AI collectible represents confirmation that the NFT was created with his permission. To manage this process, Alethea uses the “AI Protocol: a proprietary and ownership layer for generative AI now available at Polygon.” Nailwal commented: “I have seen firsthand how Alethea AI has developed this technology over the past few years and through its CharacterGPT AI engine… We are excited to continue to support Alethea as it builds on Polygon and the power and potential of AI.” to life.” Ahmad Matyana, COO of Alethea AI, gave some examples of possible use cases for the new technology: “users can now create interactive, intelligent characters that could serve as AI companions, digital guides or NPCs in games.” Influencer-based hope The company also hopes that public figures will use the AI engine to create “digital twins” of themselves “to serve as digital companions for their fans.” Because the assets can be trained, digital assets can also be used in the metaverse, games, museums, sports stadiums, and other real-world locations to interact with users and act as virtual guides.