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Europe accelerates AI drug discovery as DeepMind spinoff targets trials this year - Related to as, yet?, space, engineers, india’s

Europe accelerates AI drug discovery as DeepMind spinoff targets trials this year

Europe accelerates AI drug discovery as DeepMind spinoff targets trials this year

Google DeepMind spinoff Isomorphic Labs expects testing on its first AI-designed drugs to begin this year, as tech startups race to turn algorithmic magic into actual treatments.

“We’ll hopefully have some AI-designed drugs in clinical trials by the end of the year,” the firm’s Nobel Prize-winning CEO Demis Hassabis told a panel at the World Economic Forum in Davos this week. “That’s the plan.”.

The potential of AI-powered drug discovery is huge. Instead of spending years or even decades testing chemicals by hand, machine learning algorithms can sift through mountains of data to spot patterns and. Predict which molecules could make the next miracle drug. This could lead to faster drug development, cheaper costs, and new cures.

By one estimate, there are over 460 AI startups currently working on drug discovery. Of which over a quarter come from Europe. Globally, more than $60bn has been invested into the space so far, and. The funding flood isn’t showing any signs of letting up.

Yet discovering the drugs is merely one step in the process. it’s only when big pharma decides they’re worth manufacturing, marketing, and distributing that it’ll make a real difference to the likes of you and me.

That’s what makes some of the recent hookups between pharma behemoths and. AI startups particularly exciting.

Last year, Isomorphic Labs inked a $45mn deal with Eli Lilly to collaborate on AI-based research into small molecule therapeutics. Under the agreement, Isomorphic is also eligible to receive up to $ in “performance-based milestones.” The organization also signed a similar collaboration with Swiss biotech Novartis.

“We’re already working on real drug programs,” Hassabis told Bloomberg Television in an interview shortly following the announcements. “I would expect in the next couple of years the first AI-designed drugs in the clinic.”.

Exscientia, which spun out from Dundee University in 2012. Was among the first to apply AI to drug discovery. In 2024, the business advanced its first AI-designed drug candidate into human clinical trials. Achieving this milestone in just 12 months — a process that typically takes around five years. US rival Recursion acquired the Oxford-based business for $688mn in November.

In relation to this, these are two big examples of an AI-driven drug discovery market that’s booming, and. Increasingly, consolidating. However, there are also plenty of early-stage companies working on more niche applications of the technology. These include Cambridge, UK-based CardiaTec, which is using AI to find new drugs to treat heart conditions, and London-headquartered Multiomic Health. Which is working on formulas to treat metabolic diseases.

Despite all the potential though, AI isn’t a silver bullet for drug discovery. While it can drastically speed up finding the right compounds needed to make new drugs, the most time-consuming steps — like wet lab tests with physical samples, clinical trials. And FDA approvals — aren’t going anywhere. Still, AI’s real power lies in that critical first phase: zeroing in on targets that might’ve otherwise slipped through the cracks, saving researchers time and possibly even unlocking new treatments.

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Why India’s Best Space Engineers Are Choosing to Stay Back

Why India’s Best Space Engineers Are Choosing to Stay Back

The Indian space sector, once dominated by government-led initiatives, is seeing a surge in private players, opening up career trajectories that didn’t exist. Along with that, the decade-old norm of space engineers studying in India, gaining experience at ISRO, and then moving abroad for improved opportunities is also fading away.

Instead, more Indian engineers are choosing to stay and. Build in India.

One of the catalysts for this shift has been India’s evolving space policy. “If you recall, in 2020, Nirmala Sitharaman showcased approximately ₹20 lakh crore as part of the COVID package. A portion of that was dedicated to opening up new sectors for increased employment and investments—space was one of them,” showcased Yashas Karanam, co-founder and COO of Bellatrix Aerospace, in an .

The announcement triggered confidence, leading to a wave of private space ventures. Which in turn created jobs and opportunities that could compete with global offers.

India boasts over 190 space startups, a significant jump from just a handful in 2015. Karanam expressed that companies are not only building satellite technologies but also innovating in propulsion, launch systems. And AI-driven space navigation.

“In 2012, there was probably one corporation. In 2015, there were three. By 2017-18, it was up to 10. But after 2019-2020, the acceleration has been significant,” noted Karanam.

The investments tell the same story: Indian private space startups have collectively raised over $350 million in funding in the past five years, demonstrating both investor confidence and. A growing market.

This expansion is keeping engineers engaged in the country. “Now the opportunities are getting advanced here in India,” Karanam explained. “There are really exciting challenges to solve, and in terms of the trade-off, people went abroad because of advanced projects and financial incentives. But if you are paid well here, you could visit those countries while still building in India.”.

In terms of talent. Karanam believes India has the right set of people. “I feel we are really good with what it takes to build a space enterprise or space products because the engineers we have got have been really good. A lot of times, training or onboarding onto particular technologies would be required, but everybody is a quick learner as far as we have seen,” he stated.

Karanam observes an emerging trend within this space boom. Which is the migration of former ISRO scientists to the private sector. Unlike earlier, where ISRO was seen as the only credible player, today’s engineers, many of who have worked on India’s high-profile missions, are stepping out to start their own companies.

“We have seen more people quitting their ISRO jobs and. Starting up on their own because they now know that the government is supporting this sector,” Karanam noted. “India also realised that despite being one of the top five global spacefaring nations, we had less than 2% of the global commercial market share. That was because only ISRO was doing it.”.

This realisation has fueled a policy shift that encourages private participation, resulting in companies securing contracts directly from ISRO and. IN-SPACe (India’s nodal space authorisation body). The industry, once restricted to working under ISRO’s guidance, is now developing independent solutions for both domestic and international clients.

Bengaluru-based aerospace manufacturer Bellatrix Aerospace, which specialises in developing in-space propulsion systems and. Small satellite manufacturing, was founded in 2015 by Rohan M Ganapathy and Karanam. Since its inception, Bellatrix has raised a total of $ million over four funding rounds.

Some of its notable investors include Inflexor, Pavestone, StartupXseed, GrowX. BASF, and others. Bollywood actress Deepika Padukone has also backed Bellatrix.

Furthermore, this Indian private space startup has developed two innovative satellite propulsion systems: a water-based Microwave Plasma Thruster and India’s first private Hall Effect Thruster. Positioning the country as a leader in innovative propulsion technology.

Despite the enthusiasm, India’s space startups face a significant hurdle: building hardware at scale. While software-based AI and deep-tech companies can scale quickly with limited capital, space hardware requires heavy upfront investment, regulatory approvals. And access to cutting-edge materials.

Karanam elaborated on the challenges of building space components domestically. “If I were to build a propulsion system, I could buy a valve from a corporation that makes valves, buy propellant from a propellant manufacturer, and buy a catalyst from Shell or SABIC.

“But if all my suppliers are outside India, and I have to import everything, paying space shipping and. Customs duty, it does not make sense in the long term,” he presented.

As a result, companies are increasingly choosing to manufacture components in-house. “We were blessed with a really capable team, and we had several retired ISRO scientists advising us. So, we took the bold decision to build even materials in-house,” Karanam added.

While building space hardware is a challenge. Funding for hardware development is a major roadblock. Most investors, accustomed to rapid returns from SaaS and consumer-tech startups, hesitate to back capital-intensive deep-tech ventures.

“There is a funny saying: ‘The space industry is a sinkhole for money.’ The more you deploy, the more it goes into capital and. R&D,” Karanam said, reflecting on investor scepticism. Unlike software, which can show quick user growth and revenues, hardware requires patience, long development cycles, and extensive testing.

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Is Samsung sweating yet? Honor just unveiled its 'Alpha Plan' at MWC 2025

Is Samsung sweating yet? Honor just unveiled its 'Alpha Plan' at MWC 2025

At the Mobile World Congress 2025, Honor revealed a series of new hardware, but that was arguably the least essential thing. Instead, the focus on software, especially AI applications that may just strike a chord with customers, stole the show.

Also: What to expect at MWC 2025: Best phones I'm anticipating from Xiaomi, Honor, Samsung. More.

At the event, Honor revealed what it calls "Alpha Plan," an initiative to transition the smartphone brand into an AI device ecosystem corporation. This is accompanied by an extended software support promise, matching that of Samsung and Google, and three new IoT launches. Here's the full rundown of the Sunday newsbreak.

A closer collaboration with Google and Qualcomm.

With Alpha Plan, Honor says it'll invest $10 billion over the next five years for a "renewed focus on open collaboration." The corporation says it'll work closely with Google and Qualcomm to co-create an "intelligent ecosystem," a series of devices that can seamlessly communicate and interact with each other -- like what Apple has arguably achieved, but improved.

This collaboration will also help Honor deliver seven years of Android OS and security updates to its flagship smartphones. Joining the likes of Samsung and Google in terms of software longevity.

Also: This 5-year tech industry forecast predicts some surprising winners - and losers.

Building on these developments, the Honor Magic 7 Pro and Magic 7 RSR will be the first two devices to be included in the new enhancement standard. Unfortunately, Honor won't offer these many updates to its latest foldable, the Magic V3, but the firm has assured that upcoming Magic series phones will receive the seven years of Android OS updates.

Honor also presented a new AIMAGE imaging brand. Which includes a new feature for restoring old portraits. It'll roll out for the Magic 7 Pro later this month. AIMAGE is powered by the AI Kernel and is presented to support a billion parameter model to "generate a 50% uplift in image clarity." The business will soon release its AI Deepfake detection feature to its flagship smartphones. We'll surely want to test the accuracy and reliability of it, but it's a practical tool nonetheless during a time of digital confusion.

Like Oppo's O+ Connect, Honor has also presented a new way to transfer data between Android and. Apple-owned platforms. For example, a new iOS app called Honor Connect will allow customers to transfer data (files, images, and videos) between Honor devices and. An iPhone seamlessly.

New wearables and a tablet for the global market.

Honor is expanding its product lineup in Europe with three new devices. Leading the charge are the Honor Earbuds Open, a pair of open-ear wireless earbuds designed with a built-in ear hook -- similar in style to the recent Beats Powerbeats Pro.

Weighing grams per earbud, they offer a secure fit while integrating AI-powered capabilities such as Live Translation and. An AI agent. The earbuds also include a three-microphone hybrid active noise cancellation system that should help minimize wind noise and enhance voice clarity. Battery life is rated at up to six hours on a single charge, with the case extending it to 22 hours. The Honor Earbuds Open are priced at 149 euros.

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

The firm is also launching the Watch 5 Ultra. A premium smartwatch with a AMOLED display that supports an always-on mode. Its design resembles the OnePlus Watch 3, and it weighs grams. The watch is built with a titanium alloy case and a ceramic-like back cover, available in Black with a fluoroelastomer strap and Brown with a leather strap.

With an IP68 rating for dust and water resistance and. 5ATM water submersion support, the Watch 5 Ultra is built for durability. It runs Honor's custom software instead of Wear OS and is powered by a 480mAh battery, delivering up to 15 days of battery life. The smartwatch is priced at 279 euros.

Last but not least, Honor has also presented a new tablet called the Pad V9. It sports an LCD with support for a 144Hz refresh rate and a sharp 1,840 x 2,800-pixel resolution. It is powered by the MediaTek Dimensity 8350 Elite chipset, paired with up to 12GB of RAM and 256GB of storage.

Also: This $500 Android tablet beat my iPad Pro in almost every way - and it's not a Samsung.

The Honor Pad V9 packs a 10,100mAh battery. Which can be expected to last you a couple of days. At 475 grams, the Pad V9 should be comfortable to use. On the front, you get an 8MP camera for video calls, and a 13MP rear camera takes care of the scanning needs. It is priced at 250 euros.

Unlike previous years, Honor hasn't revealed a new smartphone at MWC. Instead, it's focusing on AI and delivering a enhanced software experience. Seven years of software support is promising, and it's safe to say the Google Cloud and Qualcomm collaborations are only just getting started.

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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 Europe Accelerates Drug 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:

algorithm intermediate

algorithm

generative AI intermediate

interface

API beginner

platform 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.

platform intermediate

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

large language model intermediate

API

machine learning intermediate

cloud computing