Alphabet’s self-driving unit, Waymo, has announced plans to expand testing of its autonomous driving technology into over 10 new cities by 2025. The company highlighted successful adaptation of its Waymo Driver system in diverse environments, encouraging this expansion. Current test sites include destinations such as Michigan’s Upper Peninsula and Tokyo, with new testing set to include San Diego and Las Vegas, among other yet-to-be-revealed locations.
The testing process will begin with manual driving through high-traffic and complex areas, including city centres and freeways. Trained human specialists will oversee the vehicles during this phase. Each city will host fewer than 10 vehicles for several months to collect data and refine the technology. Waymo previously expanded its autonomous ride-hailing service to Miami, Florida, as part of its broader strategy to capture market share in the competitive autonomous vehicle industry.
Waymo’s growth comes as the firm faces heightened scrutiny from regulators following incidents involving autonomous driving systems. In October, the company secured $5.6 billion in funding led by parent company Alphabet, aimed at bolstering its technological advancements and operational expansion.
General Motors is pivoting towards its advanced driver assistance system, Super Cruise, after shutting down its loss-making robotaxi business. The technology, similar to Tesla’s Autopilot, enables hands-free driving and is now available on around 20 high-end models, including Cadillacs and large SUVs. GM expects the system to generate $2 billion in annual revenue within five years.
Unlike traditional car sales, Super Cruise provides an ongoing revenue stream through subscriptions. Customers receive three years of free access before being charged $25 per month or $250 per year. The technology relies on a sophisticated combination of cameras, radar, and driver-monitoring sensors to ensure safety, offering a more robust system than Tesla’s.
Despite this push into software-driven revenue, GM’s stock has yet to see the kind of growth Tesla enjoys. Investors remain cautious, especially amid concerns over potential tariffs on Canada and Mexico. However, CEO Mary Barra remains optimistic, aiming to double the number of Super Cruise-enabled vehicles in 2025 and significantly increase subscription renewals.
SoftBank is set to invest $500 million in SkildAI, a fast-growing AI robotics startup, at a valuation of $4 billion. The company, founded just two years ago, specialises in building AI models that can be adapted for different robotic applications. Previous investors include Jeff Bezos, Lightspeed Venture Partners, and Coatue Management, who contributed to a $300 million round last July.
The investment comes amid surging interest in AI-powered robotics, with major backers like Bezos ramping up funding in the sector. Startups such as Physical Intelligence and Figure AI have also secured hundreds of millions in recent months to develop advanced robotic “brains” and humanoid robots.
SkildAI’s latest funding highlights the growing competition in AI-driven automation, with investors betting on smarter, more adaptable robots. As demand for robotics expands across industries, firms like SkildAI are positioning themselves at the forefront of this technological revolution.
Figure AI has announced the creation of the Centre for the Advancement of Humanoid Safety, a new initiative aimed at ensuring humanoid robots can operate safely in workplaces. Led by former Amazon Robotics safety engineer Rob Gruendel, the centre will focus on testing AI-controlled robots for stability, human detection, and navigation to minimise accidents.
The rise of humanoid robots in warehouses and factories has sparked concerns about their potential risks. Unlike traditional industrial robots, which were confined to cages, these machines move freely among workers, raising safety questions. Existing solutions, such as Amazon’s wearable safety vest and Veo Robotics’ vision-based systems, have helped, but regulation remains largely absent.
Figure AI plans to release regular safety reports detailing its progress, testing methods, and solutions for potential hazards. As companies push to integrate humanoid robots into daily operations, and eventually, into homes, the need for clear safety standards is becoming increasingly urgent.
The digital revolution has brought in remarkable innovations, and quantum computing is emerging as one of its brightest stars. As this technology begins to showcase its immense potential, questions are being raised about its impact on blockchain and cryptocurrency. With its ability to tackle problems thought to be unsolvable, quantum computing is redefining the limits of computational power.
At the same time, its rapid advancements leave many wondering whether it will bolster the crypto ecosystem or undermine its security and decentralised nature. Can this computing breakthrough empower crypto, or does it pose a threat to its very foundations? Let’s dive deeper.
What is quantum computing?
Quantum computing represents a groundbreaking leap in technology. Unlike classical computers that process data in binary (0s and 1s), quantum computers use qubits, capable of existing in multiple states simultaneously due to quantum phenomena such as superposition and entanglement.
For example, Google’s new chip, Willow, is claimed to solve a problem in just five minutes—a task that would take the world’s fastest supercomputers approximately ten septillion years—highlighting the extraordinary power of quantum computing and fuelling further debate about its implications.
These advancements enable quantum machines to handle problems with countless variables, benefiting fields such as electric vehicles, climate research, and logistics optimisation. While quantum computing promises faster, more efficient processing, its intersection with blockchain technology adds a layer of complexity so the story takes an interesting twist.
How does quantum computing relate to blockchain?
Blockchain technology relies on cryptographic protocols to secure transactions and ensure decentralisation. Cryptocurrencies like Bitcoin and Ethereum use elliptic curve cryptography (ECC)to safeguard wallets and transactions through mathematical puzzles that classical computers cannot solve quickly.
Quantum computers pose a significant challenge to these cryptographic foundations. Their advanced processing power could potentially expose private keys or alter transaction records, threatening the trustless environment that blockchain depends upon.
Opportunities: Can crypto benefit from quantum computing?
While the risks are concerning, quantum computing offers several opportunities to revolutionise blockchain:
Enhanced security: Developers can leverage quantum principles to create stronger, quantum-secure algorithms.
Smarter decentralisation: Quantum-powered computations could enhance the functionality of smart contracts and decentralised apps (DApps).
By embracing quantum advancements, the blockchain industry could evolve to become more robust and scalable— hopefully great news for the crypto community, which is optimistic about the potential for progress.
How does quantum computing threaten cryptocurrency?
Despite its potential benefits, quantum computing poses significant risks to the cryptocurrency ecosystem, depending on how it is used and who controls it:
Breaking public key cryptography Quantum computers equipped with Shor’s algorithm can decrypt ECC and RSA encryption. Tasks that would take classical computers millennia could be accomplished by a quantum computer in mere hours. This capability threatens to expose private keys, allowing hackers to access wallets and steal funds.
Mining oligopoly The mining process, vital for cryptocurrency creation and transaction validation, depends on computational difficulty. Quantum computers could dominate mining activities, disrupting the decentralisation and fairness fundamental to blockchain systems.
Dormant wallet risks Wallets with exposed public keys, particularly older ones, are at heightened risk. A quantum attack could compromise these funds before users can adopt protective measures.
With projections suggesting that quantum computers capable of breaking current encryption standards could emerge within 10–20 years—or perhaps even sooner—the urgency to address these threats is intensifying.
Solutions: Quantum-resistant tokens and cryptography
Where there is a challenge, there is a solution. The crypto industry is proactively addressing quantum threats with quantum-resistant tokens and post-quantum cryptography. Lattice-based cryptography, for example, creates puzzles too complex for quantum computers, with projects like CRYSTALS-Kyber leading the charge. Hash-based methods, such as QRL’s XMSS, ensure data integrity, while code-based cryptography, like the McEliece system, uses noisy signals to protect messages. Multivariate polynomial cryptography also adds robust defences through complex equations.
As we can see, promising solutions are already actively working to uphold blockchain principles. These innovations are crucial not only for securing crypto assets but also for maintaining the integrity of blockchain networks. Quantum-resistant measures ensure that transaction records remain immutable, safeguarding the trust and transparency that decentralised systems are built upon.
The quantum future for crypto
Quantum computing holds tremendous promise for humanity, but it also brings challenges, particularly for blockchain and cryptocurrency. As its capabilities grow, the risks to existing cryptographic protocols become more apparent. However, the crypto community has shown remarkable resilience, with quantum-resistant technologies already being developed to secure the ecosystem. This cycle of threats and solutions is a perpetual motion—each technological advancement introduces new vulnerabilities, met with equally innovative defences. It is the inevitable price to pay for embracing the modern decentralised finance era and the transformative potential it brings.
The future of crypto does not have to be at odds with quantum advancements. With proactive innovation, collaboration, and the implementation of quantum-safe solutions, blockchain can survive and thrive in the quantum era. So, is quantum computing a threat to cryptocurrency? The answer lies in our ability to adapt. After all, with great power comes great responsibility—and opportunity.
Chinese AI startup DeepSeek has announced that its Janus-Pro-7B model has surpassed competitors, including OpenAI’s DALL-E 3 and Stability AI’s Stable Diffusion, in benchmark rankings for text-to-image generation. This achievement solidifies DeepSeek’s reputation as a key player in the rapidly evolving AI market.
According to a technical report, the Janus-Pro model builds upon its predecessor by incorporating enhanced training processes, higher-quality data, and advanced scaling, resulting in improved stability and more detailed image outputs. The company credited the inclusion of 72 million high-quality synthetic images, combined with real-world data, for the model’s superior performance.
This success follows the launch of DeepSeek’s new AI assistant based on the DeepSeek-V3 model, which has become the top-rated free app in the US Apple App Store. The news sent shockwaves through the tech industry, leading to declines in shares of companies like Nvidia and Oracle, as investors reassessed the competitive dynamics in AI development.
OpenAI and Stability AI have yet to comment on the claims. DeepSeek’s achievements highlight the growing influence of Chinese firms in cutting-edge AI innovation, setting the stage for heightened competition in the global tech market.
AI-powered study rooms are revolutionising online education in China by offering personalised, tech-driven learning experiences. These spaces cater to students aged 8 to 18, using advanced software to provide interactive lessons and real-time feedback. The AI systems analyse mistakes, adjust course materials, and generate detailed progress reports for parents, who can track their child’s improvement remotely. By leveraging technology, these study rooms aim to make education more engaging and tailored to individual learning needs.
These AI rooms are marketed as self-study spaces rather than traditional tutoring centres, allowing them to navigate China’s strict private tutoring regulations by framing their services as facility rentals or membership plans. This creative positioning allows them to operate within a regulatory grey area, avoiding restrictions on off-campus tutoring for students in grades one through nine. Membership fees range from 1,000 to 3,000 yuan monthly, making them a more affordable long-term alternative to expensive one-on-one tutoring sessions.
Despite their growing popularity, education experts remain sceptical of their educational value. Critics argue that many of these systems lack proper AI functionality, relying instead on preloaded prompts and automated responses. Furthermore, there are concerns that their heavy emphasis on drilling questions to improve test scores may neglect critical thinking and deeper comprehension. However, proponents believe these AI-powered study rooms represent an essential step toward integrating technology into education and expanding access to personalised learning.
The CEO of Japanese IT giant NTT DATA has called for global standards in AI regulation to mitigate the risks posed by the rapidly advancing technology. Speaking at the World Economic Forum in Davos, Switzerland, Abhijit Dubey emphasised that inconsistent regulations could lead to significant challenges. He argued that standardised global rules are essential for addressing issues like intellectual property protection, energy efficiency, and combating deepfakes.
Dubey pointed out that the key to unlocking AI’s potential lies not in the technology itself, which he believes will continue to improve rapidly, but in ensuring businesses are prepared to adopt it. A company’s ability to leverage AI, he said, depends on the readiness of its workforce and the robustness of its data architecture.
He stressed that companies must align their AI strategies with their broader business objectives to maximise productivity gains. ‘The biggest issue isn’t the technology it’s whether organisations are set up to implement it effectively,’ Dubey noted.
The discussion at Davos highlighted the urgent need for collaboration among governments, businesses, and industry leaders to create cohesive AI regulations that balance innovation with risk management.
Meta’s new Ray-Ban smart glasses, featuring a Live AI assistant, promise a futuristic way to interact with the world. Users can ask questions about their surroundings, with the AI offering answers in real time. From recipe ideas to decorating advice, Live AI aims to be a virtual assistant that sees what you see and responds conversationally.
Despite its intriguing potential, Live AI struggles in everyday use. Its responses often state the obvious, like suggesting scrambled eggs when a fridge has two eggs and no milk. Users also find it challenging to remember to use the feature, with a smartphone search frequently feeling more practical and efficient. Moreover, the AI’s suggestions often lack the depth needed to be genuinely useful.
Making Live AI effective requires users to master the art of asking precise, specific questions a skill that doesn’t come naturally to everyone. This, combined with issues like misinterpreting conversations and a short battery life, makes the technology feel less magical in real-world scenarios. While the glasses point to a vision of hands-free AI, they currently struggle to provide a compelling alternative to existing devices.
A robotic puppy named ‘Jennie’ is offering a new way to provide companionship to people living with dementia, anxiety, and other mental health challenges. Developed by Tombot, Jennie is an AI-powered pet designed to mimic the comfort and emotional support of a real dog without the difficulties of pet care. Inspired by Tombot CEO Tom Stevens’ personal experience with his mother’s Alzheimer’s diagnosis, the robotic puppy was created to help reduce loneliness and distress.
Jennie stands out with her lifelike design, a collaboration with Jim Henson’s Creature Shop, best known for the Muppets. Equipped with advanced touch sensors and voice command technology, Jennie responds naturally to petting and verbal instructions, creating a realistic experience for users. Her sound effects, crafted from recordings of Labrador puppies, and an all-day battery life make her a practical and emotionally engaging alternative to traditional pets.
Research supports Jennie’s role in easing symptoms like agitation and hallucinations in dementia patients while also helping reduce anxiety and loneliness in broader mental health contexts. With over 7,500 preorders already received, Jennie’s impact is growing as Tombot explores registering her as a medical device, potentially expanding her reach to hospitals and care facilities worldwide.
Priced around $1,500, Jennie offers an accessible solution for those unable to care for live animals due to health or housing constraints. The US based company continues to improve Jennie’s capabilities with software updates, ensuring this robotic puppy remains a dynamic source of comfort for years to come.
