The cut-off dates for holiday shopping have mostly passed, but that doesn't mean the deals have disappeared. We're seeing prices that match Black Friday, like the Beats Fit Pro for just $160 and Bose's QuietComfort Earbuds II for $249. Some items have even dipped below their Cyber Week prices, like GoPro's Hero 11 Black Mini, the 13.3-inch MacBook Pro and Eufy's RoboVac X8 Hybrid. While these items may not ship out in time to wrap them up as gifts, this is still a great opportunity to grab devices and tech you've had your eye on, and save a little in the process. Here are the best deals from the week that you can still get today.

Developing and training successful machine learning (ML) fraud models requires access to large amounts of high-quality data. Sourcing this data is challenging because available datasets are sometimes not large enough or sufficiently unbiased to usefully train the ML model and may require significant cost and time. Regulation and privacy requirements further prevent data use or sharing even within an enterprise organization. The process of authorizing the use of, and access to, sensitive data often delays or derails ML projects. Alternatively, we can tackle these challenges by generating and using synthetic data.

Retail supply chains are under immense pressure to keep up with these rapid changes. Innovators have been quick to take advantage of the new virtual distributed environment. Also, e-commerce is growing at an unprecedented rate and customers expect faster delivery times and more personalized service. And retailers are facing pressure to keep costs down and increase profitability. Despite these challenges, organizations can take action and make a difference.

Shoppers are returning to stores especially as society learns to live with the pandemic. During the start of the 2022 holiday season, the number of shoppers going back to physical stores well exceeded the expectations of the National Retail Federation. But stores continue to face the reality of not having enough store associates to manage the foot traffic. A study from UKG finds many U.S.-based retail stores are struggling to meet sales goals because they are short staffed (80 percent, up from 68 percent in 2021). The study says customers will likely feel the impact of these labor challenges when shopping for the holidays (72 percent).

Dr Anastasia Griva is exploring real-world phenomena in the AI and business analytics space, looking to answer questions that are important to society. Dr Anastasia Griva received her PhD in business analytics from the Athens University of Economics and Business three years ago. This was an industry-funded PhD and she worked closely with the retail sector, while establishing two AI and analytics start-ups. But academia was her dream and so she joined the University of Galway as a post-doc researcher. She applied successfully for a Marie Skłodowska-Curie fellowship through Lero, the Science Foundation Ireland research centre for software. After this, she obtained her first academic position as a lecturer, and she is now the programme director for the MSc in business analytics at the University of Galway.

Dec 15 (Reuters) - ChatGPT, the new chatbot that is the talk of Silicon Valley, can spit out haikus, crack jokes in Italian and may soon be the scourge of teachers everywhere facing fake essays generated by the AI-powered technology. But a question it can't fully answer is this: How will OpenAI make money? The research organization, co-founded by Elon Musk and investor Sam Altman and backed by $1 billion in funding from Microsoft Corp (MSFT.O), is expecting its business to surge. Three sources briefed on OpenAI's recent pitch to investors said the organization expects $200 million in revenue next year and $1 billion by 2024. The forecast, first reported by Reuters, represents how some in Silicon Valley are betting the underlying technology will go far beyond splashy and sometimes flawed public demos.

If you operate in a country with multiple official languages or across multiple regions, your audio files can contain different languages. Participants may be speaking entirely different languages or may switch between languages. Consider a customer service call to report a problem in an area with a substantial multi-lingual population. Although the conversation could begin in one language, it's feasible that the customer might change to another language to describe the problem, depending on comfort level or usage preferences with other languages. With a minimum of 3 seconds of audio, Amazon Transcribe can automatically identify and efficiently generate transcripts in the languages spoken in the audio without needing humans to specify the languages.

Welcome to insideBIGDATA's annual technology predictions round-up! The big data industry has significant inertia moving into 2023. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives. Even if only half actually come true, Big Data in the next year is destined to be quite an exciting ride. There are many reasons why a customer would choose to implement their architecture on multiple clouds whether it's technology, market, or business-driven. When this happens, many times this leads to transactional and operational data being stored on multiple cloud platforms. The challenge this brings is how to gain insight into these without resorting to implementing multiple disparate data platforms. Historically data virtualization tools have been ...

On this weblog, we introduce the rising significance of MLOps and the MLOps accelerator co-developed by Walgreens Boots Alliance (WBA) and Databricks. The MLOps accelerator is designed to standardize ML practices, scale back the time to productionize ML mannequin, increase collaboration between knowledge scientists and ML engineers, and generate enterprise values and return of funding on AI. All through this submit, we clarify the purposes of MLOps on the Databricks Lakehouse Platform, how WBA automates and standarizes MLOps, and how one can replicate their success. MLOps, the composition of DevOps DataOps ModelOps, is a set of processes and automation to assist organizations handle code, knowledge, and fashions. However placing MLOps into observe comes with its challenges. In machine studying (ML) methods, fashions, code, and knowledge all evolve over time, which might create friction round refresh schedules and ML pipelines; in the meantime, mannequin efficiency could degrade over time as knowledge drifts requiring the mannequin to be retrained.

Check out all the on-demand sessions from the Intelligent Security Summit here. A shopper is perusing the Lands' End website -- either because they are loyal to the brand, occasionally buy items when they're on sale, or happened there after Googling around for, say, a down winter coat with a fur-lined hood. Maybe they make a purchase, maybe they don't. But if they opt to provide their email, they might soon be alerted that doggy puffer vests and squall jackets are on sale (because they perused them thinking they might look cute on their dog); or that their favorite country star Blake Shelton has a new item in his Lands' End clothing line. This is the type of personalized experience the retailer hopes to provide with its new partnership with Movable Ink. Lands' End announced today that it will leverage Movable Ink's AI-powered Da Vinci platform to bolster the retailer's email marketing program.