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Symbolica Launches with $33M Funding to Transform the AI Industry with Symbolic Models

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Today, the artificial intelligence startup Symbolica AI made its debut, introducing a novel method for creating generative AI models.

The company is aiming to tackle the expensive mechanisms behind training and deploying large language models such as OpenAI’s ChatGPT that are based on Transformer architecture.

In addition to that announcement, the company disclosed today that it has raised $33 million in total capital from a seed and Series A funding round headed by Khosla Ventures. Day One Ventures, Abstract Ventures, Buckley Ventures, and General Catalyst were among the other investors.

Transformer deep learning architectures have surpassed all other types, particularly for large language models, as demonstrated by numerous examples such as Google LLC’s Gemini, Anthropic PBC’s Claude, and OpenAI’s ChatGPT. That’s because of their widespread use and the abundance of tools available for their creation and implementation, despite the fact that they are very costly and complex. In addition, they require enormous amounts of energy and data, are challenging to validate, and have a propensity to “hallucinate,” which is the term for when a model confidently presents an incorrect assertion as fact.

Unlike Transformers, which use the contextual and statistical relationships between inputs and learn from previously given content, Symbolica builds AI models through structured models that define tasks through manipulating symbols. Symbolic AI uses symbols to represent a set of rules, which enables them to be pretrained for specific tasks like word processing or coding.

Based on the idea of “categorical deep learning,” the startup applies structured mathematics to define the relationship between symbols. It provided clarification in a paper that it and Google DeepMind co-authored recently. When compared to large, complex unstructured models like GPT, structured models require less overall data and can operate on less computing power because they classify and encode the underlying structure of the data.

“Regime-specific structured reasoning abilities can be generated in significantly smaller models by combining advances in deep learning with a rich mathematical toolbox,” stated George Morgan, CEO of Symbolica, in an interview with TechCrunch.

The company plans to create a toolkit that will enable the creation of “interpretable” models—meaning that users will be able to decipher the reasoning behind the AI network’s decisions. This should increase the transparency of the models, making it much easier for developers to monitor and debug them.

For highly regulated industries like healthcare and finance, where inaccuracy risks could have disastrous consequences, interpretability is essential for developing better AI in the future. To apply transparency for regulatory audits, it is also critical to comprehend an AI’s knowledge base and decision-making process.

The company’s first product, a coding assistant, will launch in early 2025, according to Morgan, who spoke with Reuters. This is because the company needs to build and train its model first.

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Coforge and Microsoft Establish Copilot Innovation Hub to hasten the Deployment of Generative AI

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Global supplier of digital services and solutions Coforge Limited recently announced a partnership with Microsoft to launch the Coforge Copilot Innovation Hub. In addition to working closely with Microsoft to integrate these solutions with Microsoft’s generative AI products and technologies, such as Microsoft Azure OpenAI Service, Microsoft Power Platform, and Microsoft Copilot, the Hub will concentrate on building a pipeline of new, industry-specific cognitive analytics solutions.

Coforge announced the launch of two new copilots as part of the Copilot Innovation Hub: Underwriter Copilot for insurance companies and Advisor Copilot for financial services firms. An innovative technique to improve ROI and streamline the process of navigating the complexity of underwriting, the Underwriter Copilot for Insurance gives insurance underwriters more authority and the ability to make informed decisions. The goal of the solution is to increase carriers’ combined ratios by two to three percent in order to open up new income streams. Insurance carriers can achieve a 30- to 35 percent boost in underwriter productivity and efficiency by implementing Underwriter Copilot.

By removing the need for time-consuming searches across several tools, documents, and data sources, the Coforge Advisor Copilot solution gives financial quick access to full fund information and performance data through an intuitive interface. Financial advisers and asset managers should become more productive by more than thirty percent thanks to the solution.

According to Sudhir Singh, Executive Director & CEO of Coforge, “Coforge is leveraging its deep industry strengths and customer partnerships to build industry specific generative AI solutions on the Microsoft platform to drive transformation and enhance productivity.” Our efforts to provide our clients with generative AI solutions that lead the market will go even faster thanks to our partnership with Microsoft. He went on, “We are announcing two new copilots today: Advisor Copilot for financial services businesses and Underwriter Copilot for insurance carriers.

“Our combined commitment to transforming and scaling organizational capabilities of financial services firms globally is demonstrated by the Coforge Copilot Innovation Hub. The 2024 Work Trend Index Annual Report states that 75% of individuals utilize AI at work, and that the use of generative AI has nearly doubled in the last six months. According to David Smith, Vice President, WW Channel Sales, Microsoft, “Coforge and Microsoft are dedicated to spearheading AI adoption, fostering innovation, and unleashing business value for businesses worldwide.”

Through the automation of manual chores, the improvement of decision-making through the creation of suggestions based on corporate data, and the streamlining and optimization of business processes, these copilots will increase operational efficiency by utilizing Microsoft’s generative AI products and technologies. These solutions will help businesses generate new value streams and speed up change.

Microsoft’s generative AI products will be easier to implement with the Coforge Copilot Innovation Hub, leading to increased productivity and better business results.

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Samsung Appoints New Leader for Chip Unit as AI Competition Intensifies

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As the race to build artificial intelligence processors heats up, Samsung Electronics has replaced the leader of its semiconductor division.

In an unexpected announcement made by the business on Tuesday, Vice Chairman Jun Young-hyun has been named head of Samsung’s device solutions division. The company’s foundry, memory, and system semiconductor divisions are managed under the device solutions division.

“Vice Chairman Jun Young-hyun is the key player who took Samsung Electronics’ memory semiconductor and battery businesses to the global top-tier level,” the company stated in a news release.

Samsung is making this announcement as it battles to overtake its regional rival SK Hynix in the market for AI memory chips. When it comes to high-bandwidth memory (HBM) chips, which are essential for AI computing, SK Hynix is in the lead.

According to Samsung, if the board and shareholders approve, Jun may also be named as the company’s chief executive. Samsung has two chief executive officers: one leads the company’s semiconductor division, while the other oversees its mobile and visual display businesses.

Before taking on the role of chief executive of Samsung SDI, the company’s battery division, Jun led Samsung’s memory chip business team for three years, from 2014 to 2017. In 2000, he made his debut as a member of Samsung’s memory chip business team.

Kyung Kye-hyun, who oversaw the semiconductor branch since2022, is replaced by Jun. During the memory chip market collapse, the division under his direction reported billion-dollar losses. The 61-year-old Kyung has been posting lengthy and in-depth posts on social media platforms like LinkedIn and Instagram about subjects including technology and climate change.

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Kudos Secures $10.2 Million for Its AI-Powered Smart Wallet

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The Four Cities Fund, Samsung Next, SV Angel, Precursor Ventures, The Mini Fund, Newtype Ventures, Patron, and The Points Guy creator Brian Kelly all participated in the funding round.

Kudos, an app and browser extension, was founded in 2001 by a group with prior expertise at Google, PayPal, and Affirm. It functions as a smart wallet assistant by suggesting or choosing the best credit card for customers to use when making payments in order to optimize rewards and cash back.

Recently, the company introduced a number of new features: Dream Wallet, which suggests cards to members based on their spending patterns; MariaGPT, an AI-powered card discovery tool with over 3000 cards in its database; and Kudos Boost, which offers personalized rewards across over 15,000 partner brands, such as Walmart and Sephora.

Since its initial fundraising round, Kudos has raised its annualized checkout Gross Merchandise Value to $200 million and expanded to over 200,000 registered users.

It intends to use the additional funds to develop MariaGPT into a comprehensive personal finance assistant, introduce an AI-powered hub offering expenditure optimization insights, and create a gateway that lets users book flights using points.

As consumers budgets, various credit cards, and sometimes complex rewards programs, they want to know they’re receiving the best value for their money, according to Tikue Anazodo, CEO of Kudos. With just one user-friendly app and extension, Kudos streamlines everything.”

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