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Everything you need to know about Alexa+, Amazon's new generative AI assistant

Everything you need to know about Alexa+, Amazon's new generative AI assistant

Amazon has been focused on bringing generative AI to Alexa for the past few years. Hitting multiple delays in launching new aspects that the enterprise first presented in September 2023. The delayed Alexa was poised for a 2025 release, and Amazon held a late February event where it made big announcements for the artificial intelligence-powered virtual assistant.

Amid rumors of Alexa shortcomings, Amazon skipped its 2024 Devices and Services event. Where the organization typically announces new Alexa attributes and hardware devices. Instead, it unveiled Alexa+ last month, the voice assistant's generative AI attributes, and finally put an ETA on its launch.

Also: 7 exciting AI elements coming with Alexa+ (and what Amazon devices support it).

"Up until a couple of years ago, it was pretty difficult to invent with AI, and. That changed with the arrival of foundational models and generative AI. This made the technology much more accessible, so people can see the power and magic of what generative AI can do," Amazon CEO Andy Jassy mentioned.

The event. Which took place on Feb. 26 in New York City, was Panos Panay's first since joining the Devices and Services division after his Microsoft exit. In addition to new Alexa elements, Amazon also made other announcements.

Everything introduced at Amazon's February 2025 event.

Giving Alexa the power of generative AI was already expected to be the star announcement from Amazon -- and. It was. During the last Devices and Services event in 2023, Amazon showcased a gen AI-powered 'Alexa+' or Alexa Plus and a new user interface coming to an Echo device near you, and the firm is now making it more real than ever before.

Panay likened the evolution of Alexa and its obstacle-ridden road toward generative AI to a symphony warming up before a concert and how the conductor raises the baton to transform "disconnected sounds into a masterpiece."

Alexa+ will reply with a more natural cadence. Handle multiple prompts in a session, and generate content instead of providing canned answers to questions. It will also feature greater customization power to remember user preferences (think like ChatGPT's Memory) for more productive user interactions, learning "the rhythm of your life," .

Also: Not all Echo devices will get Alexa+ initially - see if yours made the list.

Aside from all of this, Alexa+ has contextual awareness. So it can hold long conversations and remember what you asked before your last questions instead of giving canned responses from Alexa Answers contributors. As Amazon demoed, it can also read and process documents for you to answer questions, like school calendars or an HOA CC&R document.

The new Alexa+ will begin rolling out next month to some customers in an early access manner, with a gradual rollout after that.

Amazon expressed little about the new Alexa after the 2023 event. With rumors suggesting that the organization was repeatedly forced to delay its gen AI launch due to deficient performance. Thankfully, Amazon seems to have finally smoothed out its Alexa .

While Alexa dominates the US market for virtual assistants, preferred by two-thirds of Americans, it has also not long ago fallen behind other assistants. Including Google and, most not long ago, Siri. The release of OpenAI's ChatGPT in recent years triggered a tidal wave of generative AI that pushed other virtual assistants ashore. At the same time, Alexa appears to have sunk to the bottom of the ocean -- until now.

Also: Here's how to use Alexa+ for free - especially if you're an Amazon Prime member.

Building on these developments, the new breed of gen AI-powered virtual assistants -- ChatGPT and Microsoft Copilot powered by OpenAI's technologies, Google Assistant-powered by Gemini. And Siri powered by Apple LLMs -- have surged ahead in the past two years. We can only wait to see how well the new Alexa+, powered by Amazon Bedrock models, including Nova and Anthropic, will perform in real-world scenarios.

The "Classic Alexa" will still be available for customers who prefer not to pay the monthly fee. Though it's not known how long Amazon plans to maintain the current version.

Amazon also showcased a new revamped platform for the Echo Show with the launch of Alexa+. The new look in the Echo Show interface seems like it will be available in the larger Echo Show displays for now. Alexa+ will also have integrations with your Ring subscriptions to provide a new experience on the Echo Show.

The redesigned Echo Show user interface elements a sleeker layout for your favorite widgets and. A cohesive look throughout the screen. Alexa+ is bringing adaptive display to the large Echo Show devices, the Echo Show 15 and Echo Show 21, to show a simplified view from afar that transitions to a customized screen when you approach the device.

As a general rule. I'm not a huge fan of talking to AI chatbots. Even though many of them sound pretty human, they're still.

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OpenAI Launches GPT-4.5, Runs Out of GPUs

OpenAI Launches GPT-4.5, Runs Out of GPUs

After weeks of waiting, OpenAI has finally introduced , its latest and largest AI language model. It was internally referred to as Orion.

It is in research preview for ChatGPT Pro clients, offering enhanced writing, knowledge. And a more natural, less hallucinatory experience. is first being made available to ChatGPT Pro clients, with Plus and Team clients gaining access next week, followed by Enterprise and. Education clients.

“ is ready,” posted OpenAI CEO Sam Altman on X. “It is a giant, expensive model. We really wanted to launch it to plus and pro at the same time, but we’ve been growing a lot and are out of GPUs.”.

Altman presented that tens of thousands of GPUs will be added next week for the Plus tier, with hundreds of thousands more coming soon, all of which are expected to be fully utilised.

In the recent NVIDIA earnings call, CEO Jensen Huang mentioned the organization’s inference demand is accelerating, fuelled by test-time scaling and. New reasoning models.

“Models like OpenAI’s, Grok 3, and DeepSeek R1 are reasoning models that apply inference-time scaling. Reasoning models can consume 100 times more compute,” he expressed.

was only trained with pretraining, supervised finetuning, and. RLHF, so this is not a reasoning model. It is an extension of the GPT series of models, unlike the o series of models.

, the pricing for input tokens is $ per million tokens. While cached input tokens are available at a reduced rate of $ per million tokens. The cost for output tokens is $ per million tokens.

“This isn’t a reasoning model and won’t crush benchmarks. It’s a different kind of intelligence and there’s a magic to it I haven’t felt before.” added Alman.

The model is more computationally efficient, and offers a tenfold improvement over GPT-4.

In the livestream, the OpenAI team outlined the evolution of GPT models – from GPT-1 was barely coherent, to became the first truly useful model, to continuing this trend with incremental enhancements.

lately. Anthropic released its Claude Sonnet and xAI launched its Grok 3, competing in the same space.

Altman had previously presented the roadmap for GPT-5. OpenAI’s goal is to combine its large language models to eventually create a more capable model that could be labeled as artificial general intelligence, or AGI.

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This Shark Tank-Featured Bengaluru Startup is Tackling ‘Lazy Eye’ with VR Therapy

This Shark Tank-Featured Bengaluru Startup is Tackling ‘Lazy Eye’ with VR Therapy

Amblyopia, often referred to as ‘lazy eye’, is a prevalent yet frequently overlooked vision disorder that affects 1-5% of the global population. Its prevalence has reached up to 5% in India. While conventional therapies exist and have proven effective, they come with numerous challenges and are often met with resistance, especially from young children. A Bengaluru-based health-tech startup is using immersive virtual reality to address this issue.

Founded in 2023. NeuraSim uses advanced VR-based simulations to rewire the brain’s visual processing. It offers a breakthrough alternative to traditional treatments for amblyopia, such as patching therapy.

“The conventional therapy is called patching, where we put a patch over the good eye and. Let the brain be forced to use the weaker eye. This takes nine months, and children often drop out within two to three months. In contrast, our immersive therapy improves vision starting from 20 days of therapy, with results in 45 days,” mentioned Ramesh S Ve, founder and. CEO of NeuraSim, in an .

Amblyopia usually occurs in childhood when one eye is significantly weaker than the other. This leads the brain to suppress input from the weaker eye. If left untreated, it can result in permanent vision impairment.

NeuraSim’s VR therapy offers a non-invasive, engaging, and scientifically validated approach. By immersing patients in controlled VR environments, the treatment stimulates the weaker eye while simultaneously ensuring the brain integrates inputs from both eyes.

“We need to dissociate one eye as being weak and. The other as being strong. The brain is conditioned to only use one eye, and we have to recondition it and rewire it. Virtual reality, by design, brings in that facility,” Ramesh noted.

The therapy consists of immersive VR simulations customised for each patient’s needs. The technology has been validated through clinical testing, and the results are promising.

“To our surprise, within 45 sessions. From near blindness in the weak eye, a seven-year-old child gained almost 600% improvement. Today, that child has stable vision which she wouldn’t otherwise have had,” Ramesh shared.

Furthermore, this form of treatment also addresses the shortage of ophthalmologists and. Optometrists in the country. “For India’s billion population, we just have around 30,000 ophthalmologists and 25,000-30,000 optometrists. Even if we include opticians and other support staff, the total workforce is just about one lakh. This is nowhere near enough to provide adequate eye care for the growing population,” Ramesh emphasised.

NeuraSim, founded in 2023 and headquartered in Bengaluru. Has its research and development incubated at the Manipal Bioincubator. The firm initially received funding from a Biotechnology Industry Research Assistance Council (BIRAC) grant and later secured a €1 million Indo-European research grant to develop its VR technology.

NeuraSim’s VR solution is built on years of research and. Clinical trials. Ramesh, who has a background in public health and vision science, worked with leading institutions like Johns Hopkins University and. Manipal Academy of Higher Education before founding NeuraSim with Girish Somvanshi. His extensive experience in epidemiological studies and telehealth inspired the creation of the startup.

Despite being a relatively young startup and even in recent times getting featured in Shark Tank India, where they failed to receive funding, NeuraSim has already gained traction among India’s top eye care institutions and. Received a number of inquiries following the airing of that episode.

Aravind Eye Care, an ophthalmology institution known worldwide, was among its first paying end-individuals. “We wanted to validate if there was a real business case. Today, we have over 20 end-individuals, including repeat clients from the Aravind chain,” Ramesh stated.

NeuraSim offers two pricing models for its VR-based amblyopia therapy. One of the models includes a monitor, mini-computer, and VR device and is priced at ₹ lakh. For this variant, therapy is administered by a clinician. Meanwhile, the second model is available for rent at ₹12,000 per month. “That comes to around ₹200 per session, making it more accessible for parents who would otherwise spend ₹400 on travel for clinic visits,” he further stated.

While VR-based vision therapy presents great promise. The road to adoption doesn’t come without its challenges. One of the primary hurdles was the availability of suitable VR hardware.

Initially, NeuraSim relied on imported devices like Pico. Which later became difficult to procure due to geopolitical issues. This pushed the organization to partner with Pune-based startup Question What’s Real (QWR) to manufacture VR headsets locally.

“We are very proud to say that we are now hardware agnostic. Our software can work on QWR devices, Oculus Quest, and other VR platforms. But as a medical device business, we need a hardware partner who can support regulatory compliance and long-term servicing,” Ramesh noted.

By transitioning to domestic hardware partners, the organization has managed to cut costs by nearly a third. Making the solution more affordable.

Moreover, parental scepticism about VR-based therapy posed an initial barrier. Many parents questioned whether extended VR exposure was safe for children.

“We explain that this is a temporary, structured treatment, not long-term VR exposure. It’s like a prescription, a controlled use of VR to improve vision function,” he clarified.

Looking ahead. NeuraSim aims to expand its VR therapy offering beyond amblyopia. The startup is developing AI-based retinal imaging tools and neurorehabilitation programs for conditions such as glaucoma and Parkinson’s disease. The organization’s roadmap also includes expanding its clinical partnerships, increasing accessibility through home-based therapy solutions, and. Entering international markets.

“Our target is to be in 150-200 clinics by December 2025. Each clinic treating at least five patients per month for home therapy will allow us to reach a scale where vision therapy becomes more accessible,” Ramesh outlined.

With the rising number of patients, AI, telehealth, and VR-based therapy can help bridge the gap in healthcare access, ensuring more people receive timely treatment despite the shortage of specialists – a vision NeuraSim is actively working towards.

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Market Impact Analysis

Market Growth Trend

2018201920202021202220232024
23.1%27.8%29.2%32.4%34.2%35.2%35.6%
23.1%27.8%29.2%32.4%34.2%35.2%35.6% 2018201920202021202220232024

Quarterly Growth Rate

Q1 2024 Q2 2024 Q3 2024 Q4 2024
32.5% 34.8% 36.2% 35.6%
32.5% Q1 34.8% Q2 36.2% Q3 35.6% Q4

Market Segments and Growth Drivers

Segment Market Share Growth Rate
Machine Learning29%38.4%
Computer Vision18%35.7%
Natural Language Processing24%41.5%
Robotics15%22.3%
Other AI Technologies14%31.8%
Machine Learning29.0%Computer Vision18.0%Natural Language Processing24.0%Robotics15.0%Other AI Technologies14.0%

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity:

Innovation Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity AI/ML Blockchain VR/AR Cloud Mobile

Competitive Landscape Analysis

Company Market Share
Google AI18.3%
Microsoft AI15.7%
IBM Watson11.2%
Amazon AI9.8%
OpenAI8.4%

Future Outlook and Predictions

The Everything Need Know landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:

Year-by-Year Technology Evolution

Based on current trajectory and expert analyses, we can project the following development timeline:

2024Early adopters begin implementing specialized solutions with measurable results
2025Industry standards emerging to facilitate broader adoption and integration
2026Mainstream adoption begins as technical barriers are addressed
2027Integration with adjacent technologies creates new capabilities
2028Business models transform as capabilities mature
2029Technology becomes embedded in core infrastructure and processes
2030New paradigms emerge as the technology reaches full maturity

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:

Time / Development Stage Adoption / Maturity Innovation Early Adoption Growth Maturity Decline/Legacy Emerging Tech Current Focus Established Tech Mature Solutions (Interactive diagram available in full report)

Innovation Trigger

  • Generative AI for specialized domains
  • Blockchain for supply chain verification

Peak of Inflated Expectations

  • Digital twins for business processes
  • Quantum-resistant cryptography

Trough of Disillusionment

  • Consumer AR/VR applications
  • General-purpose blockchain

Slope of Enlightenment

  • AI-driven analytics
  • Edge computing

Plateau of Productivity

  • Cloud infrastructure
  • Mobile applications

Technology Evolution Timeline

1-2 Years
  • Improved generative models
  • specialized AI applications
3-5 Years
  • AI-human collaboration systems
  • multimodal AI platforms
5+ Years
  • General AI capabilities
  • AI-driven scientific breakthroughs

Expert Perspectives

Leading experts in the ai tech sector provide diverse perspectives on how the landscape will evolve over the coming years:

"The next frontier is AI systems that can reason across modalities and domains with minimal human guidance."

— AI Researcher

"Organizations that develop effective AI governance frameworks will gain competitive advantage."

— Industry Analyst

"The AI talent gap remains a critical barrier to implementation for most enterprises."

— Chief AI Officer

Areas of Expert Consensus

  • Acceleration of Innovation: The pace of technological evolution will continue to increase
  • Practical Integration: Focus will shift from proof-of-concept to operational deployment
  • Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
  • Regulatory Influence: Regulatory frameworks will increasingly shape technology development

Short-Term Outlook (1-2 Years)

In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing ai tech challenges:

  • Improved generative models
  • specialized AI applications
  • enhanced AI ethics frameworks

These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.

Mid-Term Outlook (3-5 Years)

As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:

  • AI-human collaboration systems
  • multimodal AI platforms
  • democratized AI development

This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.

Long-Term Outlook (5+ Years)

Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:

  • General AI capabilities
  • AI-driven scientific breakthroughs
  • new computing paradigms

These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.

Key Risk Factors and Uncertainties

Several critical factors could significantly impact the trajectory of ai tech evolution:

Ethical concerns about AI decision-making
Data privacy regulations
Algorithm bias

Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.

Alternative Future Scenarios

The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:

Optimistic Scenario

Responsible AI driving innovation while minimizing societal disruption

Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.

Probability: 25-30%

Base Case Scenario

Incremental adoption with mixed societal impacts and ongoing ethical challenges

Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.

Probability: 50-60%

Conservative Scenario

Technical and ethical barriers creating significant implementation challenges

Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.

Probability: 15-20%

Scenario Comparison Matrix

FactorOptimisticBase CaseConservative
Implementation TimelineAcceleratedSteadyDelayed
Market AdoptionWidespreadSelectiveLimited
Technology EvolutionRapidProgressiveIncremental
Regulatory EnvironmentSupportiveBalancedRestrictive
Business ImpactTransformativeSignificantModest

Transformational Impact

Redefinition of knowledge work, automation of creative processes. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.

The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.

Implementation Challenges

Ethical concerns, computing resource limitations, talent shortages. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.

Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.

Key Innovations to Watch

Multimodal learning, resource-efficient AI, transparent decision systems. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.

Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.

Technical Glossary

Key technical terms and definitions to help understand the technologies discussed in this article.

Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.

Filter by difficulty:

large language model intermediate

algorithm

generative AI intermediate

interface

reinforcement learning intermediate

platform

platform intermediate

encryption Platforms provide standardized environments that reduce development complexity and enable ecosystem growth through shared functionality and integration capabilities.

interface intermediate

API Well-designed interfaces abstract underlying complexity while providing clearly defined methods for interaction between different system components.

API beginner

cloud computing APIs serve as the connective tissue in modern software architectures, enabling different applications and services to communicate and share data according to defined protocols and data formats.
API concept visualizationHow APIs enable communication between different software systems
Example: Cloud service providers like AWS, Google Cloud, and Azure offer extensive APIs that allow organizations to programmatically provision and manage infrastructure and services.