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CityUHK neuroscientist crack code on brain multitasking, uncovering neural mechanisms behind cognitive bottlenecks

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HONG KONG, Sept. 3, 2026 /PRNewswire/ — It is commonly perceived that multitasking is highly inefficient, with the brain often “crashing” or scrambling when trying to do two things at once. A study co-led by Professor Yung Wing-ho, Chair Professor in the Department of Neuroscience at City University of Hong Kong (CityUHK), together with scholars from The Chinese University of Hong Kong, has explained the underlying cause, revealing how the brain dynamically reorganises itself to break through the cognitive bottleneck and achieve efficient, simultaneous multitasking.

The study confirms at the cellular level the brain’s remarkable ability to adapt and optimise its neural resources, overturning the public’s understanding of its parallel processing capacity and providing insights into the neural mechanisms that allow humans to balance flexibility and specialisation in daily life. The findings were published in the leading neuroscience journal Neuron, under the title “Dynamic coordination and segregation mechanisms in higher cortex for parallel task processing“.

To investigate how the brain handles two tasks at the same time, the research team utilised an innovative mouse model to observe the brain’s secondary motor cortex (M2) during dual-task performance. Mice had to maintain a continuous lever movement task while listening to different auditory cues and deciding whether to respond, a sensory decision-making task known as a “Go/No-Go” test. Using longitudinal two-photon calcium imaging, the researchers tracked the activity of the same individual neurons within a large neuronal population in M2 over several weeks of training, allowing them to observe how neural activity was reorganised as the animals learned to multitask.

The study showed that multitasking interference can be traced at the level of individual neurons. Neurons involved in both tasks became hotspots of competition, providing a cellular basis for the brain’s limited capacity to process competing demands. The competition, however, was not confined to neurons shared by both tasks. Even neurons mainly responsible for one task adjusted their activity when the other task was being processed, helping the brain coordinate the two competing demands and achieve early multitasking success.

With continued training, the brain adopted a different strategy. More task-specific neurons were recruited, while the neural representations of the two tasks became progressively separated, allowing the tasks to progress more independently with less interference and boosting overall multitasking performance.

The team further showed that M2 plays a causal role in this learning process. When M2 activity was moderately suppressed during training, the animals failed to improve with practice. Once the suppression was removed, their multitasking performance rapidly improved.

In addition to biological observations, the research team ran simulations using recurrent neural networks. They found that simply separating the representations of the two tasks was not the most effective solution; learning was faster when early coordination was preserved while other task representations became progressively separate. This finding coincides with the strategy observed in the biological brain and offers significant implications for the development of artificial intelligence.

Professor Yung said, “Our findings suggest that efficient multitasking requires a delicate balance between coordination and specialisation. These principles may provide a framework for understanding multitasking deficits in neurological disorders and, importantly, offer a biologically inspired strategy for designing artificial intelligence systems that can learn and manage multiple competing tasks more efficiently.”

Understanding these dynamic brain processes opens new avenues for enhancing cognitive function and human potential. Moving forward, the team will leverage these insights to optimise learning strategies in education, develop more effective rehabilitation programmes for neurological conditions and continue to explore potential applications in other fields.

 

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SOURCE CITY UNIVERSITY OF HONG KONG

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Ally Waste Acquires Swift Integrated Services, Expanding Service Capabilities and Market Reach

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September 3, 2026

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GILBERT, Ariz., Sept. 3, 2026 /PRNewswire/ — Ally Waste, a nationwide provider of comprehensive waste solutions for multifamily communities, announced today that it has acquired Swift Integrated Services, a Utah-based provider of dumpster management, doorstep trash pickup, and waste brokerage services.

“Every acquisition we make starts with the same question: Will it help us serve customers better? Swift expands our reach and brings capabilities that allow us to support more of our customers’ waste needs. We’re excited to welcome the Swift team to Ally and build on what they’ve created,” said James Crawley, CEO of Ally Waste.

The acquisition expands Ally Waste’s presence in Utah, Florida, and Idaho markets while strengthening the company’s waste stream optimization capabilities. It also brings waste brokerage capabilities to Ally, giving current customers another way to address their waste needs as the offering is integrated.

“Joining Ally gives us the opportunity to build on what we’ve created while bringing our customers the support and resources of a nationwide team,” said Indigo Schumann-Curtis, President of Swift Integrated Services. “Our customers can expect business as usual, with many of the same people continuing to support them. I’m excited about what our teams can accomplish together.”

Swift Integrated Services customers can expect continuity in both service and support throughout the transition. The Swift team will continue with Ally, bringing established customer relationships and deep market knowledge to the combined organization.

About Ally Waste

Ally Waste is a nationwide provider of comprehensive waste solutions for multifamily communities, including valet trash and recycling, bulk removal, and waste stream optimization services. Its technology gives owners and operators clear visibility into what they’re paying for waste across a portfolio, paired with on-the-ground teams who put those insights into action.

The company’s culture is grounded in its values of Integrity, Grit, and Humility. These principles drive Ally Waste’s commitment to supporting multifamily teams and delivering consistent, high-quality service that improves everyday life for residents and on-site staff. Learn more at www.allywaste.com.

Media Contact:
Doridé Uvaldo
duvaldo@allywaste.com

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SOURCE Ally Waste

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Gupshup Launches Self-Serve Voice AI Platform, Extending Conversational Engagement into Phone Calls

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September 3, 2026

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Businesses can now build, test, and deploy AI voice agents across support, sales, and operations – alongside WhatsApp, RCS, and SMS – from a single platform

MUMBAI, India and SAN FRANCISCO, Sept. 3, 2026 /PRNewswire/ — Gupshup launched its Voice AI Platform, a self-serve console for building and running AI voice agents that handle calls end to end. The launch extends Gupshup’s engagement platform from messaging into voice, bringing support, sales, and operations onto the same infrastructure businesses use for WhatsApp, RCS, and SMS.

Gupshup’s Voice AI Platform resolves support calls, qualifies and converts leads, and automates operational calls such as scheduling, verification, and payment reminders, so human teams can focus on conversations that require a person.

The platform covers agent lifecycle in a no-code, prompt-based interface. Businesses configure an agent’s voice, language, knowledge base, system prompt, and workflows, then connect it to tools their teams use. Before going live, teams define guardrails, run simulations, and validate behaviour with tests – comparing models. Once deployed, analytics track success rates, satisfaction, and language usage, with transcripts, conversation history, and debug logs for review.

Gupshup’s platform is the first to bring unique capabilities. First, voice is a channel extension of a platform serving businesses across WhatsApp, RCS, and SMS – enabling voice-and-messaging experiences within a customer journey. Second, it supports telephony: PSTN and WhatsApp voice channels, on-premise and cloud deployment, and the option to bring PSTN infrastructure. Third, it is model-flexible – businesses choose speech-to-text, text-to-speech, and LLM providers rather than accepting a stack.

The platform builds on Gupshup’s experience powering customer engagement for 50,000+ businesses across 100+ countries and 25+ industries, processing 10 billion interactions monthly, including 500 million voice calls per month.

The Voice AI Platform has been beta tested and delivered outcomes across deployments. Users receive 100 minutes of credits to test, and pricing starts at USD 0.035 (INR 3.50) per minute.

“For customer engagement in emerging markets, Voice AI drives universal access – reaching every user regardless of language or literacy. In developed markets, it drives efficiency and automation. In both, it delivers cost savings, revenue growth, and satisfaction. With the launch of its Voice AI Platform alongside its messaging, Gupshup offers the only unified self-serve platform for customer engagement across voice and messaging,” said Beerud Sheth, Co-founder and CEO, Gupshup.

The Voice AI Platform is available to businesses at voiceai.gupshup.io.

For more information, visit www.gupshup.ai.

 

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SOURCE Gupshup Technology India Pvt Ltd

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Deepdub Launches Phantom Z 3.4 Conversational: Multilingual Text-to-Speech Built to Survive Real Customers, Not Just Demos

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September 3, 2026

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Enterprise-grade real-time text-to-speech delivers 150ms time to first audio at full 48 kHz, with text normalization that gets account numbers, invoice totals and appointment dates right

TEL AVIV, Israel, Sept. 3, 2026 /PRNewswire/ — Deepdub, a foundational voice AI company pioneering expressive voice technologies, announced today the launch of Phantom Z 3.4 Conversational, a new multilingual text-to-speech model with high-fidelity 48 kHz audio, improved text normalization and extended Hebrew support. The model is available to all Deepdub clients now.

For enterprises running voice agents, a call holds together when four things go right at once. The voice sounds like a person. The response arrives fast enough to feel like a conversation. The agent knows when to speak and when to listen. And every account number, date and amount comes out the way a customer would say it. When one of them slips, the call escalates to a human, and that is where containment and cost are decided. Phantom Z 3.4 Conversational is built for all four.

“Every voice model sounds impressive for two minutes in a demo. Very few survive two weeks with real customers,” said Ofir Krakowski, CEO and co-founder of Deepdub. “Deployments don’t stall on the 95% a model gets right, they stall on the misread account number, the mangled surname, the one wrong digit on a live call. We built this model for that last few percent, because in production, the last few percent is the whole product.”

In English, the work is in text normalization, the step that turns written text into spoken words. A delivery date written 2024-12-31 is read as December thirty first, twenty twenty-four rather than as a run of digits. An invoice total written $1,240 is read as one thousand two hundred forty dollars. An appointment at 14:30 is read as two thirty. A reference written Chapter VII is read as chapter seven rather than as letters. These are the categories where Deepdub’s testing puts the model ahead of the other systems it was measured against. An enterprise running more than one language gets one set of behavior to test and one contract to hold rather than two.

Phantom Z 3.4 delivers an end-to-end p95 time-to-first-audio of 150 milliseconds in real-time mode at full-range 48 kHz audio, with cross-language voice transfer from under three seconds of reference audio. Deepdub builds and trains its own speech models from random rather than licensing them, which allows the company to bring a new language into production in two weeks. Deepdub covers more than fifty locales and dialects verified by local voice and language experts, inside a platform supporting more than 50 locales and dialects.

“We run Deepdub in production for live, real-time phone calls, where latency and naturalness aren’t nice-to-haves but the key factor in whether a caller stays on the line. 3.4 is the closest we’ve heard a synthetic voice come to a real person, and our callers show it: they stay longer, talk more, and engage with our agents like we’ve never seen before,” said Adir Haziza, CTO at Voiceman.

The hardest case is Hebrew, which is written without vowels, so the same letters can spell different words. The three letters of שלט are a sign read one way and a remote control read another. A model that reads one word at a time has to guess which the sentence means, and in Hebrew a wrong guess is not an accent, it is a different word that stays invisible until a customer hears it. Phantom Z 3.4 resolves this at the source. Pronunciation is decided from the whole sentence rather than word by word, and every instance of שלט in Deepdub’s Hebrew test set was read correctly. Where a brand name or a plan tier has to be said a particular way, marking it in the text is enough. Deepdub ranks first for Hebrew text-to-speech on the public TTS Arena leaderboard hosted by ivrit.ai on Hugging Face.

In Hebrew, national ID numbers, appointment dates and transaction amounts are expanded before speech, so a balance written as 1,240 ₪ is spoken in full rather than read out as digits. In blind listening tests, Phantom Z 3.4 was preferred over Deepdub’s previous Hebrew model in 71 percent of decisive comparisons.

“We needed something that would hold up consistently across a large volume of work, so we tested it thoroughly before deciding. What stood out was that the details came out right and the Hebrew was the most natural we’d heard,” said Dor Levy, Head of Jeen Talk at Jeen AI.

About Deepdub
Deepdub is the foundational voice AI model company pioneering expressive voice technologies for global enterprises across TV, film, advertising, gaming, e-learning, and AI-agent applications. The company’s international team of technology, dubbing, and linguistic experts deliver an end-to-end voice solution that preserves the emotional and cultural integrity of original content in more than 50 locales and dialects. With an advisory board that includes media leaders such as Kevin Reilly, former Chief Content Officer at HBO Max, and Emiliano Calemzuk, former President of Fox Television Studios, Deepdub is eliminating language barriers to enable the global diffusion of media on major streaming platforms like Netflix, Amazon Prime, and Hulu. Visit https://deepdub.ai or follow us on LinkedIn for more information.

Deepdub Media Contact
Zivit Katz
Deepdub
zivit.katz@deepdub.ai

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SOURCE Deepdub

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