The Need for Cognitive and Adaptive Search Engines
Modern search systems are evolving rapidly as the demand for context-aware, adaptive information retrieval grows. With the increasing volume and complexity of user queries, particularly those requiring layered reasoning, systems are no longer limited to simple keyword matching or document ranking. Instead, they aim to mimic the cognitive behaviors humans exhibit when gathering and processing information. This transition towards a more sophisticated, collaborative approach marks a fundamental shift in how intelligent systems are designed to respond to users.
Limitations of Traditional and RAG Systems
Despite these advances, current methods still face critical limitations. Retrieval-augmented generation (RAG) systems, while useful for direct question answering, often operate in rigid pipelines. They struggle with tasks that involve conflicting information sources, contextual ambiguity, or multi-step reasoning. For example, a query that compares the ages of historical figures requires understanding, calculating, and comparing information from separate documents—tasks that demand more than simple retrieval and generation. The absence of adaptive planning and robust reasoning mechanisms often leads to shallow or incomplete answers in such cases.
The Emergence of Multi-Agent Architectures in Search
Several tools have been introduced to enhance search performance, including Learning-to-Rank systems and advanced retrieval mechanisms utilizing Large Language Models (LLMs). These frameworks incorporate features like user behavior data, semantic understanding, and heuristic models. However, even advanced RAG methods, including ReAct and RQ-RAG, primarily follow static logic, which limits their ability to effectively reconfigure plans or recover from execution failures. Their dependence on one-shot document retrieval and single-agent execution further restricts their ability to handle complex, context-dependent tasks.
Introduction of the AI Search Paradigm by Baidu
Researchers from Baidu introduced a new approach called the “AI Search Paradigm,” designed to overcome the limitations of static, single-agent models. It comprises a multi-agent framework with four key agents: Master, Planner, Executor, and Writer. Each agent is assigned a specific role within the search process. The Master coordinates the entire workflow based on the complexity of the query. The Planner structures complex tasks into sub-queries. The Executor manages tool usage and task completion. Finally, the Writer synthesizes the outputs into a coherent response. This modular architecture enables flexibility and precise task execution that traditional systems lack.
Use of Directed Acyclic Graphs for Task Planning
The framework introduces a Directed Acyclic Graph (DAG) to organize complex queries into dependent sub-tasks. The Planner chooses relevant tools from the MCP servers to address each sub-task. The Executor then invokes these tools iteratively, adjusting queries and fallback strategies when tools fail or data is insufficient. This dynamic reassignment ensures continuity and completeness. The Writer evaluates the results, filters inconsistencies, and compiles a structured response. For example, in a query asking who is older than Emperor Wu of Han and Julius Caesar, the system retrieves birthdates from different tools, performs the age calculation, and delivers the result—all in a coordinated, multi-agent process.
Qualitative Evaluations and Workflow Configurations
The performance of this new system was evaluated using several case studies and comparative workflows. Unlike traditional RAG systems, which operate in a one-shot retrieval mode, the AI Search Paradigm dynamically replans and reflects on each sub-task. The system supports three team configurations based on complexity: Writer-Only, Executor-Inclusive, and Planner-Enhanced. For the Emperor age comparison query, the Planner decomposed the task into three sub-steps and assigned tools accordingly. The final output stated that Emperor Wu of Han lived for 69 years and Julius Caesar for 56 years, indicating a 13-year difference—an output accurately synthesized across multiple sub-tasks. While the paper focused more on qualitative insights than numeric performance metrics, it demonstrated strong improvements in user satisfaction and robustness across tasks.
In conclusion, this research presents a modular, agent-based framework that enables search systems to surpass document retrieval and emulate human-style reasoning. The AI Search Paradigm represents a significant advancement by incorporating real-time planning, dynamic execution, and coherent synthesis. It not only solves current limitations but also offers a foundation for scalable, trustworthy search solutions driven by structured collaboration between intelligent agents.
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Nikhil is an intern consultant at Marktechpost. He is pursuing an integrated dual degree in Materials at the Indian Institute of Technology, Kharagpur. Nikhil is an AI/ML enthusiast who is always researching applications in fields like biomaterials and biomedical science. With a strong background in Material Science, he is exploring new advancements and creating opportunities to contribute.
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Holding a virtual monopoly in a product on which the artificial intelligence boom relies should be a golden ticket. For chipmaker Nvidia, it has been. But ASML, which makes extraordinarily complex machines that etch silicon and is no less integral to the rise of AI, has found that ruling the roost can still be an up-and-down affair.
The €270bn Dutch manufacturer, which reports its earnings next week, is a sine qua non of technology; chips powering AI and even fridges are invariably etched by ASML’s kit. The flipside is its exposure to customers’ fortunes and politics.
Revenue is inherently lumpy, and a single paused purchase makes a big dent — a key difference from fellow AI monopolist Nvidia, which is at present struggling to meet demand for its top-end chips. ASML’s newest high numerical aperture (NA) systems go for €380mn; as an example of how volatile revenue can be for such big-ticket items, one delayed order would be akin to drivers holding off on buying 8,000-odd Teslas.
Initial hopes were high for robust spending on wafer fab equipment this year and next. Semi, an industry body, in December reckoned on an increase of 7 per cent this year and twice that in 2026. Jefferies, for example, now expects sales to flatline next year.
Mood music bears that out. Top chipmaker TSMC has sounded more cautious over the timing of the adoption of new high NA machines. Other big customers are reining in spending. Intel in April shaved its capital expenditure plans by $2bn to $18bn, while consensus numbers for Samsung Electronics suggest the South Korean chipmaker will underspend last year’s $39bn capex budget.
Politics is also getting thornier. Washington, seeking to hobble China’s tech prowess, has banned sales of ASML’s more advanced machines. Going further would hurt. China, which buys the less advanced but more profitable deep ultraviolet machines, typically accounts for about a quarter of sales. Last year, catch-up on orders lifted that to half.
Meanwhile, Chinese homegrown competition, given an extra nudge by US trade barriers, is evolving. Shenzhen government-backed SiCarrier, for example, claims to have encroached on ASML territory with lithography capable of producing less advanced chips.
The good news is that catch-up in this industry, with a 5,000-strong supplier base and armies of engineers, requires years if not decades. Customers, too, will probably be deferring rather than nixing purchases. The zippier machines help customers juice yields; Intel reckons it cuts processes on a given layer from 40 steps to just 10.
Over time, ASML’s enviable market position looks solid — and perhaps more so than that of Nvidia, whose customers are increasingly trying to create their own chips. Yet the kit-maker’s shares have been the rockier investment. In the past year, ASML has shrunk by a third while Nvidia has risen by a quarter; its market capitalisation is within a whisker of $4tn. That makes ASML the braver bet, but by no means a worse one.
Astrolight is developing a laser-based communications system
I’m led through a series of concrete corridors at Vilnius University, Lithuania; the murals give a Soviet-era vibe, and it seems an unlikely location for a high-tech lab working on a laser communication system.
But that’s where you’ll find the headquarters of Astrolight, a six-year-old Lithuanian space-tech start-up that has just raised €2.8m ($2.3m; £2.4m) to build what it calls an “optical data highway”.
You could think of the tech as invisible internet cables, designed to link up satellites with Earth.
The company hopes to be part of a shift from traditional radio frequency-based communication, to faster, more secure and higher-bandwidth laser technology.
Astrolight’s space laser technology could have defence applications as well, which is timely given Russia’s current aggressive attitude towards its neighbours.
Astrolight is already part of Nato’s Diana project (Defence Innovation Accelerator for the North Atlantic), an incubator, set up in 2023 to apply civilian technology to defence challenges.
In Astrolight’s case, Nato is keen to leverage its fast, hack-proof laser communications to transmit crucial intelligence in defence operations – something the Lithuanian Navy is already doing.
It approached Astrolight three years ago looking for a laser that would allow ships to communicate during radio silence.
“So we said, ‘all right – we know how to do it for space. It looks like we can do it also for terrestrial applications’,” recalls Astrolight co-founder and CEO Laurynas Maciulis, who’s based in Lithuania’s capital, Vilnius.
For the military his company’s tech is attractive, as the laser system is difficult to intercept or jam.
It’s also about “low detectability”, Mr Maciulis adds:
“If you turn on your radio transmitter in Ukraine, you’re immediately becoming a target, because it’s easy to track. So with this technology, because the information travels in a very narrow laser beam, it’s very difficult to detect.”
Astrolight
Astrolight’s system is difficult to detect or jam
Worth about £2.5bn, Lithuania’s defence budget is small when you compare it to larger countries like the UK, which spends around £54bn a year.
But if you look at defence spending as a percentage of GDP, then Lithuania is spending more than many bigger countries.
Around 3% of its GDP is spent on defence, and that’s set to rise to 5.5%. By comparison, UK defence spending is worth 2.5% of GDP.
Recognised for its strength in niche technologies like Astrolight’s lasers, 30% of Lithuania’s space projects have received EU funding, compared with the EU national average of 17%.
“Space technology is rapidly becoming an increasingly integrated element of Lithuania’s broader defence and resilience strategy,” says Invest Lithuania’s Šarūnas Genys, who is the body’s head of manufacturing sector, and defence sector expert.
Space tech can often have civilian and military uses.
Mr Genys gives the example of Lithuanian life sciences firm Delta Biosciences, which is preparing a mission to the International Space Station to test radiation-resistant medical compounds.
“While developed for spaceflight, these innovations could also support special operations forces operating in high-radiation environments,” he says.
He adds that Vilnius-based Kongsberg NanoAvionics has secured a major contract to manufacture hundreds of satellites.
“While primarily commercial, such infrastructure has inherent dual-use potential supporting encrypted communications and real-time intelligence, surveillance, and reconnaissance across NATO’s eastern flank,” says Mr Genys.
BlackSwan Space
Lithuania should invest in its domestic space tech says Tomas Malinauskas
Going hand in hand with Astrolight’s laser technology is the autonomous satellite navigation system fellow Lithuanian space-tech start-up Blackswan Space has developed.
Blackswan Space’s “vision based navigation system” allows satellites to be programmed and repositioned independently of a human based at a ground control centre who, its founders say, won’t be able to keep up with the sheer volume of satellites launching in the coming years.
In a defence environment, the same technology can be used to remotely destroy an enemy satellite, as well as to train soldiers by creating battle simulations.
But the sales pitch to the Lithuanian military hasn’t necessarily been straightforward, acknowledges Tomas Malinauskas, Blackswan Space’s chief commercial officer.
He’s also concerned that government funding for the sector isn’t matching the level of innovation coming out of it.
He points out that instead of spending $300m on a US-made drone, the government could invest in a constellation of small satellites.
“Build your own capability for communication and intelligence gathering of enemy countries, rather than a drone that is going to be shot down in the first two hours of a conflict,” argues Mr Malinauskas, also based in Vilnius.
“It would be a big boost for our small space community, but as well, it would be a long-term, sustainable value-add for the future of the Lithuanian military.”
Space Hub LT
Eglė Elena Šataitė leads a government agency supporting space tech
Eglė Elena Šataitė is the head of Space Hub LT, a Vilnius-based agency supporting space companies as part of Lithuania’s government-funded Innovation Agency.
“Our government is, of course, aware of the reality of where we live, and that we have to invest more in security and defence – and we have to admit that space technologies are the ones that are enabling defence technologies,” says Ms Šataitė.
The country’s Minister for Economy and Innovation, Lukas Savickas, says he understands Mr Malinauskas’ concern and is looking at government spending on developing space tech.
“Space technology is one of the highest added-value creating sectors, as it is known for its horizontality; many space-based solutions go in line with biotech, AI, new materials, optics, ICT and other fields of innovation,” says Mr Savickas.
Whatever happens with government funding, the Lithuanian appetite for innovation remains strong.
“We always have to prove to others that we belong on the global stage,” says Dominykas Milasius, co-founder of Delta Biosciences.
“And everything we do is also geopolitical… we have to build up critical value offerings, sciences and other critical technologies, to make our allies understand that it’s probably good to protect Lithuania.”
