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Launched by Visual Electric to free AI art creation from chat interfaces



Launched by Visual Electric to free AI art creation from chat interfaces

There are probably some similarities that you have observed if you have experimented with at least a few of the text-to-image AI art generation services that have been introduced in recent years, like Midjourney or OpenAI’s different DALL-E versions. The most notable of them all is that they all resemble chat interfaces. The application usually responds with an image embedded in a message after the user enters their text prompts.

While this point of interaction functions admirably for some clients and application engineers, certain individuals accept it is restricting and at last not what laid out craftsmen and architects need while utilizing computer based intelligence at work. However, presently San Francisco-based Visual Electric is here to offer an alternate methodology. One that the new startup — which rises up out of covertness today following a seed round last year from Sequoia, BoxGroup, and Creator Asset of an undisclosed total — accepts is preferable adjusted to visual imagination over messaging to and fro with a man-made intelligence model.

“There’s just so many workflow-specific optimizations that you need to make if you’re a graphic designer or a concept artist,” said Colin Dunn, founder and CEO of Visual Electric, in an exclusive interview with VentureBeat. “There’s a long tail of things that will make their life way easier and will make for a much better product.”

Dunn recently drove item plan and brand at the versatile site building organization Universe, and before that, filled in as head of plan at Playspace, a Google procurement.

For enterprise users, such as independent designers, in-house designers at major brands, and even “pro-sumers,” Visual Electric aims to be that “much better product” for AI art, visual design, and creativity.

The organization is intentionally not sending off its own hidden artificial intelligence picture generator AI (ML) model. Instead, it is based on the open-source Stable Diffusion XL model, which is currently the subject of a copyright lawsuit brought by artists against Stability AI, the company that developed it, as well as Midjourney and other AI art generators.

This is due to the fact that Dunn and his two co-founders, Adam Menges, chief product officer of Visual Electric and former co-founder of Microsoft acquisition Lobe; and chief technology officer Zach Stiggelbout, who was previously employed by Lobe, are of the opinion that image generation AI models are in the process of being commoditized, and that the front-end user interface will largely determine the success and failure of businesses.

“We just want to build the best product experience,” Dunn said. “We’re really model agnostic and we’re happy to swap out whatever model is going to give users the best results. Our product can easily accommodate multiple models or the next model that’s going to come out.”

What sets Visual Electric apart from Midjourney, DALL-E 3, and other AI art apps?

What sets Visual Electric apart from previous image generators? Instead of the top-to-bottom “linear” form factor of other chat-based AI art generator apps, which force users to scroll back up to see their previous generations, it allows users to generate and drag-to-move their imagery around an infinite virtual “canvas.” Clients can keep producing new arrangements of 4 pictures all at once and move them around this material any place they’d like.

“Creativity is a nonlinear process,” Dunn said. “You want to explore; you want to go down different paths and then go back up to an idea you were looking at previously and take that in a new direction. Chat forces you into this very linear flow where it’s sort of like you have a starting point and an ending point. And that’s just not really how creativity works.”

Unlike many chat interfaces, this box has been moved to the top of the screen instead of the bottom, although there is still a space for text prompts to be entered.

To assist with conquering the underlying obstacle that a few clients face — not knowing precisely exact thing to type in to provoke the computer based intelligence to inspire it to create the picture they have to their eye — Visual Electric offers a drop-down field of autocomplete ideas, like what a client finds while composing in a pursuit on Google. All of these suggestions are based on what Visual Electric has observed from early users and what produces the best images. In any case, a client is likewise allowed to veer off from these completely and type in a custom brief too.

Moreover, Visual Electric’s electronic man-made intelligence workmanship generator offers a scope of supportive extra devices for changing the brief and style of the subsequent pictures, remembering pre-set styles that emulate normal ones for the pre-man-made intelligence computerized and printed craftsmanship universes, including “marker,” “exemplary movement,” “3D render,” “digitally embellish,” “risograph,” “stained glass,” and numerous others — with recent trends being added routinely.

It puts it in more direct competition with Adobe’s Firefly 2 AI art interface, which offers similar functionality, as the user can select their image aspect ratio from buttons on the dropdown or a convenient right-rail sidebar rather than having to specify it within the prompt text. Two common examples of this are 16:9 and 5:4.

This sidebar additionally allows the client to determine prevailing varieties and components they wish to reject from their subsequent simulated intelligence created picture, likewise inputted through text.

In addition, the user can click a button to “remix” or “regenerate” their images based on their initial prompt, or they can “touch up” specific areas of the image and have the AI regenerate only those areas that they highlight using a digital brush of a size that the user can adjust, while keeping the rest of the image intact and adding to it in the same way. So, for instance, you could “touch up” the hair of your AI-generated subject and instruct the Stable Diffusion XL model to redo only that portion of the image if you didn’t like it.

Additionally, there is a built-in upscaler that can improve image resolution and detail.

“These are the tools that represent what we see as the AI-native workflow and they in the order that you use them,” Dunn said.

Pricing, the community, and early success stories

Despite the fact that Visual Electric is going public today, the company has been quietly conducting alpha testing with a few dozen designers. Dunn claims that these designers have already provided valuable feedback that will help improve the product. Additionally, Dunn says that the promising results of how Visual Electric has been used to assist in real-world enterprise workplace situations show that the company is on the right track.

Dunn referenced one client specifically — keeping the name for classification — who had a little group of creators attempting to make menus and other visual guarantee for in excess of 600 colleges.

Previously, this group would have invested bunches of their energy figuring out stock symbolism and trying to track down pictures that matched each other yet likewise addressed genuinely the things on a school’s eating corridor menu, and having to physically alter the stock symbolism to make it more precise.

With Visual Electric, they can now create brand-new images that meet the requirements of the menu and edit portions of them without using Adobe Photoshop or other alternatives.

“They’re now able to take what was a non-creative task and make it into something that is very creative, much more fulfilling, and they can do it in a tenth of the time,” Dunn claimed.

An “Inspiration” feed of AI-generated images created on the platform by other users is another important feature that Visual Electric offers. This feed, a lattice of various estimated pictures that inspires Pinterest, permits the client to float over the pictures and see their prompts. They can also import any images from the public feed into their private canvas by “remixing” them.

“This was a early decision that we made, which is we think that with generative AI there’s an opportunity to bring the network into the tool,” Dunn explained. “Right now, you have inspiration sites like Pinterest and designer-specific sites like Dribbble, and then you have the tools like Photoshop, Creative Suite and Figma. It’s always felt odd to me that these things are not unified in some way, because they’re so related to each other.”

Clients of Visual Electric can decide to draw in with this feed and add to it or not, at their tact. For undertakings worried about the security of their symbolism and works underway, Dunn guaranteed VentureBeat that the organization views security and security in a serious way, however just the “Genius” plan offers the capacity to have secretly put away pictures — all the other things is public as a matter of course.

Sending off in the U.S. today freely, Visual Electric’s valuing is as per the following: a free plan that gives you 40 generations per day at slower speeds and a license that can only be used for personal use (you can’t sell the images or use them for marketing); a standard arrangement at $20 each month or $16/month paid every year direct, which takes into consideration local area sharing, limitless ages at 2x quicker velocities, and sovereignty free business use permit; as well as a well conceived plan for $60 each month or $48/month paid yearly direct, which offers all that the last two plans offer yet additionally significantly higher goal pictures, and fundamentally, privatized ages.

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AI’s Revolutionary Effects on Startups’ Patent Analysis




AI's Revolutionary Effects on Startups' Patent Analysis

Every startup is eager to introduce the world to its next big idea. Additionally, it’s always a good idea to file for a patent in order to protect their concept from being copied or corrupted. Since patents are by definition unique, entrepreneurs must be absolutely convinced that their concept is unique before applying for one. This can be achieved by performing an exhaustive patent search beforehand. Since speed and accuracy are critical, AI has a strong case to accelerate the patent search process for startups.

The Value of Searching for and Analyzing Patents

  • One useful method for learning about market trends is to study the patent applications that are currently pending. If a single product category has several patents, it may be a competitive market meeting different consumer requirements in that industry. Finding potential technological gaps and uncharted territory is another benefit of conducting a search and analysis of patents. For example, the firm may discover that while their initial concept has been investigated, there is a chance to safeguard and market a complementary product that would appeal to the same customer base.
  • Startups can save time and money by performing a preliminary patent search to make sure that (a) their idea is not already patented or a commercial product, or (b) it does not fall under a class of products that is not eligible for patent protection. They will save the expenses and future legal headaches of having to deal with patent infringement because of this.

Recognizing The Difficulties in Doing A Patent Search

  • In every industry, searching for patents is an extremely intricate and time-consuming procedure. It is necessary to create intricate Boolean searches, sift through all of the available patent data, and identify the key elements—such as highlighting murky areas that should be sent to a lawyer for advice. In terms of taking advantage of current market opportunities, this can be counterproductive because it can take a long time.
  • It is impossible to overestimate the importance of precision in patent searches and the analysis that follows. Any inaccuracy could result in the rejection of the patent, lawsuits alleging patent infringement, and a substantial loss of time and money. assessing whether the proposed invention is simply a copy of an existing filing made by someone else, or a version with discernible variations, becomes more challenging when assessing the criteria for patent duplication.

Artificial Intelligence in Patent Analysis and Search

  • Artificial intelligence is considerably faster than humans at finding and analyzing any type of data. Previous natural language search engines were unable to decipher the meaning and intention contained in the user-provided innovation description. However, AI-driven patent search has matured and can now produce significantly improved search relevance and extremely accurate results thanks to pre-trained Large Language Models. As a result, it is the perfect solution for tasks that require a lot of time, including patent search and analysis. Startups are already moving more quickly and closer to their eventual patent registration with the help of a number of AI search and result analysis tools.
  • Search efficiency: The efficiency that AI offers to the search process is its most evident benefit. The user may “rely” on the AI search system to provide extremely accurate results in a matter of seconds, saving them the trouble of manually crafting complex search terms to comb through patent data.
  • Semantic assessments of patents can be performed by AI trained in natural language processing (NLP). This helps them to appropriately read any sections with ambiguous wording and make sense of regional variations in language. This is especially helpful when examining patent claims for various iterations of the same invention.
  • Classification algorithms: Not all patent-related information is probably arranged according to how the startup in question views the technology. The end user can be presented with a rated and classed result by training machine learning algorithms to sort the data based on relevance.
  • Visualization tools: AI can classify and highlight important information in an understandable visual report by organizing and summarizing the data. Making educated decisions and presenting findings to pertinent parties would be made simpler as a result.

AI’s Future Directions for Searching and Analyzing Patents

Artificial intelligence has many uses in the analysis and search of patents. In order to establish a single, transparent chain of information, the integration of AI with blockchain and IoT is now being investigated. Even while some of these AI apps can be pricey, new choices are being created daily, so in the end, costs will be reduced for startups with tight budgets. AI algorithms are just getting started, but they have the potential to speed up the patent registration process enormously, so firms who use them now will be the first to see their innovative ideas come to fruition.

PatSeer is an AI-based patent search engine that leads the way in innovation by allowing users to navigate the IP landscape with never-before-seen ease thanks to its rich Boolean and AI search functionalities. With the platform’s easy-to-use interface, startups can do thorough patent searches to make sure their ideas are original and eligible for patent protection.

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An Innovative Text-to-Video AI Startup Hopes to Revolutionize New York Filmmaking




An Innovative Text-to-Video AI Startup Hopes to Revolutionize New York Filmmaking

With its innovative text-to-video generator, a New York-based firm is creating waves and has the potential to completely change the entertainment and filmmaking industries in an era where creativity and technology are interacting more than ever. Though it is still in the early phases of development, this cutting-edge tool has the potential to usher in a new era of content production by enabling users to turn textual storylines into full-length movies. In addition to its potential to democratize filmmaking, the startup’s ambitious project, which makes use of cutting-edge artificial intelligence (AI), is gaining attention for its ramifications for the entertainment industry as a whole.

A Peering Into the Future of Cinema

An AI-powered platform that translates textual input to produce related visual information is at the center of this innovative project. By transforming photos into dynamic worlds, Google’s Genie is one AI model that has already started to revolutionize interactive storytelling. This technology builds on the foundation that these models have created. By making it possible to create intricate, narratively rich video content from straightforward written descriptions, the text-to-video generator seeks to go beyond this and may pave the way for a new generation of filmmakers and content producers.

Innovations in Technology and Creative Liberty

The startup’s technology uses artificial intelligence (AI) to study and comprehend character development, narrative structures, and visual storytelling methods. By doing this, it can create videos that effectively visually convey a story in addition to telling it. In order to comprehend the nuances of human creativity, complex AI algorithms and machine learning approaches have been devised and polished. Wide-ranging ramifications result from this technology, which gives people who might not have the means or technical know-how normally needed for film production previously unheard-of creative freedoms.

Difficulties and Ethical Issues

Despite the enthusiasm surrounding this technological innovation, there are many obstacles in the way of bringing the idea to fruition. Discussions are centered on ethical issues, including copyright concerns, the veracity of AI-generated content, and the effect on conventional filmmaking roles. Furthermore, it will be crucial to address these issues in a way that respects the rights of all parties involved as well as the creative process as this technology develops. The firm is dedicated to overcoming these obstacles in order to provide a framework that guarantees the ethical and responsible application of AI in the creative industries.

Unquestionably, the New York startup’s text-to-video converter has the potential to revolutionize entertainment and democratize film production as it continues to evolve. This invention has the potential to upend storytelling conventions and empower budding filmmakers alike. Such technology has an impact on marketing, virtual reality experiences, and instructional content in addition to the entertainment sector. The nexus between artificial intelligence (AI) and human creativity promises to open up new vistas and redefine storytelling as we approach this revolutionary period.

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Vietnam’s Skills In AI Help Precision Medicine Companies




Vietnam's Skills In AI Help Precision Medicine Companies

Investments in health technology, particularly in precision medicine, are benefiting from Vietnam’s quick advances in artificial intelligence and technology.

According to DealStreetAsia’s Data Vantage’s “SE Asia Deal Review: Q4 2023” report, health tech investments in Southeast Asia remained up despite the general pessimism surrounding fundraising in 2023. The sector’s startups raised $580 million from 60 agreements. Vietnam was in third place in the area with 3.9% of the investments, while firms in far larger economies like Singapore and Indonesia took home the majority of the funding for health tech.

According to analysts, there has been a surge in interest in Vietnam’s health tech sector in recent times, as there is optimism that the utilization of artificial intelligence can accelerate advancements like precision medicine.

“Vietnam has numerous promising companies in this sector, the market is still at an early stage,” said Vy Le, co-founder and general partner of the venture capital firm Do Ventures.

Precision medicine, also referred to as “personalized medicine,” creates individualized treatments for conditions like cancer, diabetes, or Alzheimer’s by using a patient’s genetic profile. Put another way, a personalized strategy based on the patient’s DNA replaces the typical one-size-fits-all approach to diagnosis and therapy. The promise of AI in this area is that people will be able to affordably sequence their genomes.

Gene Solutions is one of the precision medicine firms in Vietnam that has drawn venture capital. In its Series B funding round, the business brought in $21 million last year. According to the Data Vantage analysis, the transaction, which was led by Mekong Capital, ranked as the seventh-largest health tech deal in Southeast Asia in 2023. Mekong Capital made a $15 million investment in Gene Solutions in 2021.

DealStreetAsia revealed in September 2023 that Gene Solutions is aiming to raise $50 million in a Series C investment.

Established in 2017, Gene Solutions focuses on using DNA markers to identify the existence of specific diseases. It has aided in the detection of chromosomal abnormalities in expectant mothers, averting genetic issues, and assisting with in-vitro fertilization. It seeks to lower the cost of genetic testing and increase accessibility.

One of Gene Solutions’ competitive advantages, according to Chris Freund, founder and partner of Mekong Capital, is “how fast-moving” company. For instance, when we first invested, it was just an idea to grow outside of Vietnam. However, in the last two years, they have successfully partnered with top hospital groups and cancer institutes in [the] Philippines, Malaysia, Indonesia, Thailand, and Singapore, with partial support from a Singaporean lab.

Gene Solutions has completed more than 350,000 genetic tests in the previous five years.

GeneStory is another company in the field; Vingroup founded it in 2022 with a charter capital of 102.3 billion dong ($4.4 million). GeneStory seeks to offer “fast and comprehensive genetic testing services based on a large Vietnamese dataset, exclusively for Vietnamese people.” But in 2022, the conglomerate itself sold a confidential interest in GeneStory. In order to develop individualized health care programs, the startup provides assessments of people’s medical, physical, and dietary risks as well as hereditary characteristics.

Vietnamese venture-backed precision medicine businesses also include Genetica Company, which uses artificial intelligence (AI) to decipher DNA. The 2018-founded company received $2.5 million from Silicon Valley investors in a pre-Series A investment round in 2021.

Genetica has introduced a gene-decoding device that employs artificial intelligence (AI) to determine a person’s genetic susceptibility to respiratory virus infection.

Southeast Asia is seeing a boom in genomic research and development at the same time as interest in precision medicine. The “Harnessing Genomic Medicine and Gene NFT in Southeast Asia” report by DealStreetAsia and Genetica, published in August 2023, states that the region’s unique and diverse genetic makeup is being highlighted through the development of genomic datasets driven by both private-sector initiatives and government-supported programs.

AI has been used in healthcare for a longer period of time than in many other industries, according to Yinglan Tan, CEO and founding managing partner of Insignia Ventures Partners. Applications of AI in healthcare include risk assessment, predictive analytics, and medical imaging. He emphasized that the Asia-Pacific area, particularly Southeast Asia, presents substantial growth potential, holding a 13% share of the worldwide AI health care market.

The increasing need for individualized health care solutions is one of the main factors driving funding for precision medicine firms. Customers are looking for specialized medical solutions as they grow more health-conscious.

“As the tests become even more precise over the coming years, it will enable Gene Solutions to detect diseases with increasingly smaller DNA segments. The cost of those tests will also come down. Eventually, such tests will be affordable for the mass market in Vietnam and Southeast Asia,” said Freund of Mekong Capital.

Through a number of programs and incentives, the Vietnamese government has also been instrumental in supporting the development of precision medicine firms. With the help of the government, a favorable atmosphere for entrepreneurs has been established, drawing both domestic and foreign investors to the emerging health technology market.

Investors are conscious of the constraints, too, such as the fact that the regulatory environment for health IT businesses is still developing. “Investing in biotech companies is typically challenging for VC funds in Vietnam. This industry demands specialized funds with experts in the field,”, according to Vy Le of Do Ventures.

In addition, venture capital funds usually have an investment horizon of four to five years, but the biotech sector needs more time to succeed. This implies that additional government funding is needed. Le gave the example of South Korea, where the government runs a fund specifically intended to invest in biotech investments at different phases of development.

However, new trends in fundraising give the industry hope.

The “The State of Healthtech in SE Asia 2023” DealStreetAsia Data Vantage report discovered that from January 2020 to September 2023, 46% of the region’s health tech startups’ total deal volume and 72% of their equity funding came from investments in deep tech fields related to health care, such as genomics, molecular biology, artificial intelligence, and biometric sensing.

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