Latest news with #VQA
Associated Press
02-05-2025
- Business
- Associated Press
MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning
SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (the 'Company' or 'MicroAlgo') (NASDAQ: MLGO) announced today the launch of their latest classifier auto-optimization technology based on Variational Quantum Algorithms (VQA). This technology significantly reduces the complexity of parameter updates during training through deep optimization of the core circuit, markedly improving computational efficiency. Compared to other quantum classifiers, this optimized model has lower complexity and incorporates advanced regularization techniques, effectively preventing model overfitting and enhancing the classifier's generalization capability. The introduction of this technology marks a significant step forward in the practical application of quantum machine learning. Traditional quantum classifiers can theoretically leverage the advantages of quantum computing to accelerate machine learning tasks, but they still face numerous challenges in practical applications. Firstly, current mainstream quantum classifiers often require deep quantum circuits to achieve efficient feature mapping, which results in high optimization complexity for quantum parameters during training. Additionally, as the volume of training data increases, the computational load for parameter updates grows rapidly, leading to prolonged training times and impacting the model's practicality. MicroAlgo's classifier auto-optimization technology significantly reduces computational complexity through deep optimization of the core circuit. This approach improves upon two key aspects: circuit design and optimization algorithms. In terms of circuit design, the technology adopts a streamlined quantum circuit structure, reducing the number of quantum gates and thereby lowering the consumption of computational resources. On the optimization algorithm front, this classifier auto-optimization model employs an innovative parameter update strategy, making parameter adjustments more efficient and substantially accelerating training speed. In the training process of classifiers based on variational quantum algorithms (VQA), parameter optimization is one of the most critical steps. Generally, VQA classifiers rely on Parameterized Quantum Circuits (PQC), where updating each parameter requires computing gradients to adjust the circuit structure and minimize the loss function. However, the deeper the quantum circuit, the more complex the parameter space becomes, requiring optimization algorithms to perform more iterations to achieve convergence. Furthermore, uncertainties and noise in quantum measurements can also affect the training process, making it difficult for the model to optimize stably. Traditional optimization methods often employ strategies such as Stochastic Gradient Descent (SGD) or Variational Quantum Natural Gradient (VQNG) to find optimal parameters. However, these methods still face challenges such as high computational complexity, slow convergence rates, and a tendency to get trapped in local optima. Therefore, reducing the computational burden of parameter updates and improving training stability have become key factors in enhancing the performance of VQA classifiers. MicroAlgo's classifier auto-optimization technology, based on variational quantum algorithms, significantly reduces the computational complexity of parameter updates through deep optimization of the core circuit. It also incorporates innovative regularization techniques to enhance the stability and generalization capability of the training process. The core breakthroughs of this technology include the following aspects: Depth Optimization of Quantum Circuits to Reduce Computational Complexity: In traditional VQA classifier designs, the number of layers in the quantum circuit directly impacts computational complexity. To lower computational costs, MicroAlgo employs an Adaptive Circuit Pruning (ACP) method during optimization. This approach dynamically adjusts the circuit structure, eliminating redundant parameters while preserving the classifier's expressive power. As a result, the number of parameters required during training is significantly reduced, leading to a substantial decrease in computational complexity. Hamiltonian Transformation Optimization (HTO): Additionally, MicroAlgo introduces an optimization method based on Hamiltonian transformations. By altering the Hamiltonian representation of the variational quantum circuit, this technique shortens the search path within the parameter space, thereby improving optimization efficiency. Experimental results demonstrate that this method can reduce computational complexity by at least an order of magnitude while maintaining classification accuracy. Novel Regularization Strategy to Enhance Training Stability and Generalization Capability: In classical machine learning, regularization methods are widely used to prevent model overfitting. In the realm of quantum machine learning, MicroAlgo introduces a novel quantum regularization strategy called Quantum Entanglement Regularization (QER). This method dynamically adjusts the strength of quantum entanglement during training, preventing the model from overfitting the training data and thereby improving the classifier's generalization ability on unseen data. Additionally, an optimization strategy based on the Energy Landscape is incorporated, which adjusts the shape of the loss function during training. This enables the optimization algorithm to more quickly identify the global optimum, reducing the impact of local optima. Enhanced Noise Robustness for Real Quantum Computing Environments: Given that current Noisy Intermediate-Scale Quantum (NISQ) devices still exhibit significant noise levels, a model's noise resilience is critical. To improve the classifier's robustness, MicroAlgo proposes a technique based on Variational Quantum Error Correction (VQEC). This method actively learns noise patterns during training and adjusts circuit parameters to mitigate noise effects. This strategy markedly enhances the classifier's stability in noisy environments, making its performance on real quantum devices more reliable. MicroAlgo's classifier auto-optimization technology, based on variational quantum algorithms, successfully reduces the computational complexity of parameter updates through deep optimization of the core circuit and the introduction of novel regularization methods. This approach significantly boosts training speed and generalization capability. This breakthrough technology not only demonstrates its effectiveness in theory but also exhibits superior performance in simulation experiments, laying a crucial foundation for the advancement of quantum machine learning. As quantum computing hardware continues to advance, this technology will further expand its application domains in the future, accelerating the practical implementation of quantum intelligent computing and propelling quantum computing into a new stage of real-world utility. In an era where quantum computing and artificial intelligence converge, this innovation will undoubtedly serve as a significant milestone in advancing the frontiers of technology. About MicroAlgo Inc. MicroAlgo Inc. (the 'MicroAlgo'), a Cayman Islands exempted company, is dedicated to the development and application of bespoke central processing algorithms. MicroAlgo provides comprehensive solutions to customers by integrating central processing algorithms with software or hardware, or both, thereby helping them to increase the number of customers, improve end-user satisfaction, achieve direct cost savings, reduce power consumption, and achieve technical goals. The range of MicroAlgo's services includes algorithm optimization, accelerating computing power without the need for hardware upgrades, lightweight data processing, and data intelligence services. MicroAlgo's ability to efficiently deliver software and hardware optimization to customers through bespoke central processing algorithms serves as a driving force for MicroAlgo's long-term development. Forward-Looking Statements This press release contains statements that may constitute 'forward-looking statements.' Forward-looking statements are subject to numerous conditions, many of which are beyond the control of MicroAlgo, including those set forth in the Risk Factors section of MicroAlgo's periodic reports on Forms 10-K and 8-K filed with the SEC. Copies are available on the SEC's website, Words such as 'expect,' 'estimate,' 'project,' 'budget,' 'forecast,' 'anticipate,' 'intend,' 'plan,' 'may,' 'will,' 'could,' 'should,' 'believes,' 'predicts,' 'potential,' 'continue,' and similar expressions are intended to identify such forward-looking statements. These forward-looking statements include, without limitation, MicroAlgo's expectations with respect to future performance and anticipated financial impacts of the business transaction. MicroAlgo undertakes no obligation to update these statements for revisions or changes after the date of this release, except as may be required by law. View original content: SOURCE
Yahoo
21-02-2025
- Business
- Yahoo
Diamond Estates Wines & Spirits Reports Q3 2025 Financial Results
Niagara-on-the-Lake, Ontario--(Newsfile Corp. - February 20, 2025) - Diamond Estates Wines & Spirits Inc. (TSXV: DWS) ("Diamond Estates" or "the Company") today announced its financial results of position for the three and nine months ended December 31, 2024 ("Q3 2025 and "YTD 2025" respectively). Q3 2025 Summary: Revenue for Q3 2025 was $6.4 million, a decrease of $0.9 million, from $7.3 million in Q3 2024. The Winery division experienced an increase in sales of $1.3 million while the Agency division experienced a decrease of $2.2 million. The increase in sales in the Winery division is largely attributable to the increase in sales in the wholesale channel, mostly from D'Ont Poke the Bear and $1.0 million from the VQA wine support program. The increase in sales is a direct result of the Ontario's government announcement to expand the marketplace to convenience, grocery and big-box stores. The decrease in the Agency division was primarily driven by the loss of a key supplier in the prior year in the amount of $2.1 million and the sale of the Western Canadian Agency business which has been offset by the acquisition of Perigon Beverage Group; Gross margin1 as a percentage of revenue was 57.5% for Q3 2025 compared to 26.3% in Q3 2024 and gross margin increased by $1.8 million from $1.9 million in Q3 2024 to $3.7 million for Q3 2025. The Winery division experienced an increase of $1.9 million while the Agency declined by $0.1 million. The gross margin in the Winery division increased from 30.5% in Q3 2024 to 57.1% in Q3 2025 as a result of the VQA Wine support program and general margin increases across most skus. The gross margin at the Agency increased from 19.9% in Q3 2024 to 61.9% in Q3 2025 due to the sale of the Western Canadian Agency and the increase in commission based sales compared to third party wines and spirits; EBITDA1 increased by $5.5 million to positive $1.4 million in Q3 2025 from a negative $4.1 million in Q3 2024. Adjusted EBITDA1 increased by $2.3 million to positive $0.6 million in Q3 2025 from a negative $1.7 million in Q3 2024. Both EBITDA and Adjusted EBITDA1 increases are attributed to improving gross margins in the Winery division and an overall decrease in SG&A expenses of $0.6 million compared to the prior year; and Net income was $0.5 million, compared to a net loss of $5.2 million in Q2 2024. Subsequent Events: In February, 2025, the Company issued an aggregate of 221,875 DSUs in settlement of $44,375 of previously accrued deferred directors compensation. President's Message "The change in the Ontario alcohol landscape continues to have a dramatic impact on our Winery results and we are strategically aligned to seize the opportunity. We anticipate these changes will continue to benefit the Winery in the coming quarter and fiscal year as more grocery stores come on-line. With the potential tariffs threats fanning fierce Canadian patriotism, we expect even stronger demand for 100% locally grown and made VQA wines. We also anticipate further industry and government support to help focus consumer interest in the wines we make here. "One of our VQA brands, D'Ont Poke the Bear, is a flag bearer representing Canadian pride with it's "polite until poked" anti bullying tagline and over $250,000 in donations to support Kids Help Phone," said Andrew Howard, President and CEO. "Additionally, we are now seeing strong year-over-year improvements in our Agency business with the acquisition of Perigon Beverage Group and the additional organic growth from new business wins and our established brand representations." Andrew continued to say, "Combined, our business has posted a remarkable turnaround with dramatic year over year improvements and consistently improving results over the first three quarters of this fiscal year. As a company, we are very well positioned to benefit from new government policies and the opening up of additional grocery, big box and convenience stores." About Diamond Estates Wines and Spirits Inc. Diamond Estates Wines and Spirits Inc. is a producer of high-quality wines and ciders as well as a sales agent for over 120 beverage alcohol brands across Canada. The Company operates four production facilities, three in Ontario and one in British Columbia, that produce predominantly VQA wines under such well-known brand names as 20 Bees, Creekside, D'Ont Poke the Bear, EastDell, Lakeview Cellars, Mindful, Shiny Apple Cider, Fresh Wines, Red Tractor, Seasons, Serenity and Backyard Vineyards. Through its commercial division, Trajectory Beverage Partners, the Company is the sales agent for many leading international brands in all regions of the country. These recognizable brands include Fat Bastard, and Gabriel Meffre wines from France, Brimoncourt Champagne from France, Rossi D'Asiago Limoncello from Italy, Kaiken wines from Argentina, Blue Nun and Erben wines from Germany, Kings of Prohibition and McWilliams Wines from Australia, Yealands Family Wines and Joiy Sparkling wine from New Zealand, Cofradia Tequilas from Mexico, Maverick Distillery spirits (including Tag Vodka, Ginslinger Gin and Barnburner Whisky) from Ontario, Cavit, Talamonti and Cielo wines from Italy, Porta 6, Julia Florista, Catedral and Cabeca de Toiro wines from Portugal, Edinburgh Gin, Tamdhu, Glengoyne and Smokehead single-malt Scotch whiskies from Scotland, Islay Mist and Waterproof blended Scotch whiskies from Scotland, Glen Breton Canadian whiskies, C.K Mondavi & Family, Line 39, Harken, FitVine and Rabble wines from California & Charles Krug wines from Napa Valley, Hounds Vodka from Canada, Bols Vodka from Amsterdam, Koyle Family Wines from Chile, Rodenbach beer from Belgium, La Trappe beer from the Netherlands, and Tequila Rose Strawberry Cream, Five Farms Irish Cream Liqueur, Broker's Gin, Hussong's Tequila, 360 Vodka and Holladay Bourbon from McCormick Distilling International. Forward-Looking Statements This press release contains forward-looking statements. Often, but not always, forward-looking statements can be identified by the use of words such as "plans", "expects" or "does not expect", "is expected", "estimates", "intends", "anticipates" or "does not anticipate", or "believes", or variations of such words and phrases or state that certain actions, events or results "may", "could", "would", "might" or "will" be taken, occur or be achieved. Forward-looking statements involve known and unknown risks, uncertainties and other factors which may cause the actual results, performance or achievements of Diamond Estates Wines and Spirits Inc. to be materially different from any future results, performance or achievements expressed or implied by the forward-looking statements. Actual results and developments are likely to differ, and may differ materially, from those expressed or implied by the forward-looking statements contained in this press release. Such forward-looking statements are based on a number of assumptions which may prove to be incorrect, including, but not limited to: the economy generally; consumer interest in the services and products of the Company; financing; competition; and anticipated and unanticipated costs. While the Company acknowledges that subsequent events and developments may cause its views to change, the Company specifically disclaims any obligation to update these forward-looking statements. These forward-looking statements should not be relied upon as representing the views of the Company as of any date subsequent to the date of this press release. Although the Company has attempted to identify important factors that could cause actual actions, events or results to differ materially from those described in forward-looking statements, there may be other factors that cause actions, events or results not to be as anticipated, estimated or intended. There can be no assurance that forward-looking statements will prove to be accurate, as actual results and future events could differ materially from those anticipated in such statements. Accordingly, readers should not place undue reliance on forward-looking statements. Non IFRS Financial Measure Management uses net income (loss) and comprehensive income (loss) as presented in the unaudited interim condensed consolidated statements of net income (loss) and comprehensive income (loss) as well as "gross margin", "EBITDA" and "Adjusted EBITDA" as a measure to assess performance of the Company. The Company defines "gross margin" as gross profit excluding depreciation. EBITDA and "Adjusted EBITDA" are other financial measures and are reconciled to net income (loss) and comprehensive income (loss) below under "Results of Operations". EBITDA and Adjusted EBITDA are supplemental financial measures to further assist readers in assessing the Company's ability to generate income from operations before considering the Company's financing decisions, depreciation of property, plant and equipment and amortization of intangible assets. EBITDA comprises gross margin less operating costs before financial expenses, depreciation and amortization, non-cash expenses such as share-based compensation, one-time and other unusual items, and income tax. Adjusted EBITDA comprises EBITDA before non- recurring expenses including cost of sales adjustments related to inventory acquired in business combinations, EWG transaction costs expensed, government funding under CEWS and CERS programs, and other non-recurring adjustments included in the calculation of EBITDA. Gross margin is defined as gross profit excluding depreciation on property, plant and equipment used in production. Operating expenses exclude interest, depreciation on property, plant and equipment used in selling and administration, and amortization of intangible assets. For more information, please contact: Andrew HowardPresident & CEO, Diamond Estates Wines & Spirits Inc. ahoward@ Ryan Conte, CPA, CA, CBVCFO, Diamond Estates Wines & Spirits Neither the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release. 1 See definition of selected terms under the heading "Non-IFRS Financial Measures" To view the source version of this press release, please visit
