About graphcore
Company Description
Graphcore is a pioneering technology company focused on developing advanced machine learning and artificial intelligence solutions through its innovative hardware and software products. Headquartered in Bristol, UK, Graphcore has made significant strides in the AI space with its Intelligence Processing Unit (IPU) technology, designed to accelerate machine learning workloads and enable more sophisticated AI applications. The company fosters a collaborative and inclusive work culture that encourages creativity and innovation. Employees at Graphcore benefit from a dynamic work environment where they are empowered to experiment, learn, and grow in their careers. The company values teamwork, diversity, and a strong commitment to excellence, making it an exciting place for tech enthusiasts and professionals alike.
Software Engineer Interview Questions
Q1: Can you explain the difference between supervised and unsupervised learning?
Supervised learning involves training a model on a labeled dataset, where the output is known, allowing the model to learn the relationship between input features and output labels. Unsupervised learning, on the other hand, deals with unlabeled data, where the model tries to identify patterns and structures within the data without predefined labels.
Q2: What are some common techniques for optimizing machine learning models?
Common techniques include feature selection, hyperparameter tuning, regularization methods (like L1 and L2), and using ensemble methods such as boosting and bagging to combine multiple models for improved performance.
Q3: How do you handle missing data in a dataset?
Missing data can be addressed through various methods such as imputation (filling in missing values with mean, median, or mode), removing rows or columns with missing values, or using algorithms that support missing values without requiring imputation.
Q4: Describe your experience with distributed computing frameworks.
I have worked with distributed computing frameworks such as Apache Spark and TensorFlow, which allow for parallel processing of large datasets. This experience includes setting up clusters, optimizing data pipelines, and leveraging distributed algorithms to enhance computational efficiency.
Q5: What is your approach to debugging a complex machine learning model?
My approach includes checking data integrity, examining model architecture, analyzing loss curves, and using validation sets to evaluate performance. I also utilize logging and visualization tools to identify potential issues in the training process.
Data Scientist Interview Questions
Q1: What is the importance of data preprocessing in machine learning?
Data preprocessing is crucial as it prepares raw data for analysis, ensuring that it is clean, consistent, and suitable for the model. Proper preprocessing can significantly improve model accuracy and performance by addressing issues such as outliers, missing values, and irrelevant features.
Q2: How would you explain a complex machine learning concept to a non-technical audience?
I would use analogies and simple language to break down the concept into relatable terms. For example, I might compare a machine learning algorithm to teaching a child to recognize different animals by showing them pictures and telling them the names, thus helping them learn through examples.
Q3: Can you describe a project where you utilized machine learning to solve a business problem?
In a previous project, I developed a predictive model to forecast customer churn. By analyzing historical customer data and identifying key features, I created a model that helped the company target at-risk customers with tailored retention strategies, ultimately reducing churn by 15%.
Q4: What tools and libraries do you prefer for data analysis and why?
I prefer using Python with libraries such as Pandas for data manipulation, NumPy for numerical computations, and Matplotlib/Seaborn for data visualization. These tools are widely used, have extensive documentation, and provide efficient ways to handle data.
Q5: How do you evaluate the performance of a machine learning model?
I evaluate model performance using metrics such as accuracy, precision, recall, F1 score, and area under the ROC curve (AUC-ROC) for classification tasks. For regression tasks, I use metrics like mean absolute error (MAE) and R-squared. Cross-validation is also employed to ensure the model generalizes well to unseen data.
AI Research Scientist Interview Questions
Q1: What are the key components of a neural network?
The key components of a neural network include input layers, hidden layers, output layers, activation functions, and weights. Each layer transforms the input data through weighted connections, allowing the network to learn complex patterns.
Q2: How do you stay current with advancements in AI and machine learning?
I regularly read research papers from journals and conferences, participate in online courses, attend workshops and seminars, and engage with the AI community through forums and social media. This helps me stay informed about the latest trends and breakthroughs in the field.
Q3: Can you explain the concept of overfitting and how to prevent it?
Overfitting occurs when a model learns the training data too well, capturing noise and outliers, which can lead to poor performance on unseen data. To prevent overfitting, techniques such as cross-validation, regularization, and using simpler models, or early stopping can be effective.
Q4: Describe a challenging AI problem you have worked on and how you approached it.
I worked on a project involving natural language processing to build a sentiment analysis model. The challenge was the ambiguity of language. I addressed this by employing advanced techniques like word embeddings (Word2Vec, GloVe) and fine-tuning a transformer-based model (BERT) to capture contextual meanings effectively.
Q5: What role do you think ethics plays in AI research?
Ethics is paramount in AI research because AI systems can impact individuals and society. Responsible AI development requires transparency, fairness, and accountability to ensure that algorithms do not perpetuate biases or cause harm. Ethical considerations must guide research and deployment decisions.
Company Background and Industry Position
If you’re diving into the world of AI hardware, chances are you’ve heard of Graphcore. Founded in 2016 and headquartered in Bristol, UK, Graphcore has established itself as a pioneer in the design of Intelligence Processing Units (IPUs), specialized chips built to accelerate machine learning workloads. Unlike traditional CPUs and GPUs, these IPUs are tailored for the complex computations behind deep learning models, making Graphcore one of the leading names in the hardware for AI acceleration.
What makes Graphcore particularly notable is its strong emphasis on research-driven innovation and collaboration with both academia and industry giants. They’ve carved a niche that blends cutting-edge silicon design with software frameworks optimized to extract maximum performance. This positioning gives them a distinctive edge compared with tech giants offering AI accelerators but that don’t design hardware from the ground up.
For candidates, this means joining Graphcore is not just about working on hardware — it’s about entering the sweet spot where technology and AI meet at scale. The company’s culture and hiring ethos reflect this; they look for individuals who thrive on complexity and innovation.
How the Hiring Process Works
- Application and Initial Screening: The process begins with submitting your resume through their careers portal or via referrals. Screening focuses heavily on relevant experience, especially with AI hardware, software development, or systems design. Expect recruiters to look for specific keywords tied to Graphcore’s tech stack.
- Recruiter Call: If your profile matches, a recruiter will contact you for a preliminary discussion. This conversation gauges your general background, motivation for applying, and basic role fit. It’s also a chance for you to understand the company’s mission and culture.
- Technical Assessment: Depending on the role, you might be asked to complete a coding challenge, a hardware design problem, or a take-home assignment. This step filters candidates who have the baseline technical skills required.
- Technical Interview Rounds: Here, you’ll face several rounds (usually two to three) that dig deep into your technical expertise. Expect live problem-solving, system design discussions, and questions tailored to your domain—whether that’s software engineering, hardware architecture, or AI research.
- HR Interview: The final interview generally explores behavioral aspects, cultural fit, and your long-term aspirations. They assess communication skills, teamwork, and adaptability. Salary and benefits get discussed here as well.
- Offer and Negotiation: After successful rounds, you’ll receive an offer outlining salary range, stock options, and other perks. At this stage, there’s room for negotiation based on your experience and market benchmarks.
This layered approach ensures only candidates who align technically and culturally move forward. It’s rigorous but designed to be fair and transparent.
Interview Stages Explained
Recruiter Conversation: Setting the Stage
The recruiter chat isn’t just a formality. It’s your first real chance to tell your story and why Graphcore’s mission resonates with you. Recruiters are trained to listen for genuine enthusiasm and clarity about your career goals. This conversation also helps set expectations for the tougher rounds ahead. It’s a two-way street — candidates should use this time to ask about team dynamics, typical projects, and the company’s growth trajectory.
Technical Screening: The Gatekeeper Round
This stage weeds out those lacking essential skills. For software roles, expect coding tasks that test algorithmic thinking and familiarity with languages like Python, C++, or Rust. For hardware positions, questions might focus on circuit design principles, FPGA programming, or understanding of processor architectures. The challenges are practical, designed to mirror day-to-day problems rather than obscure puzzles.
Candidates often report it feels like solving real work scenarios with a ticking clock. Preparing by brushing up on fundamentals and hands-on practice is key.
In-depth Technical Interviews: Proving Expertise
The technical rounds are the heart of the selection process. Typically conducted by senior engineers or team leads, these interviews explore your problem-solving approach, system design skills, and domain-specific knowledge.
For example, a software engineer might be asked to architect a distributed training system optimized for Graphcore’s IPUs, blending knowledge of machine learning workflows with scalable software design. Hardware candidates could be challenged on optimizing dataflow architectures or power-performance trade-offs.
Interviewers are not just looking for correct answers but how you think and communicate complex ideas. Being transparent about your reasoning is often more impressive than a perfect solution.
HR Interview: The Cultural and Career Fit
The final step is more conversational. It focuses on your interpersonal skills, adaptability, and alignment with Graphcore’s core values: innovation, collaboration, and resilience. HR might probe for examples of past teamwork, handling setbacks, and how you stay current in such a fast-evolving field. This stage also addresses salary expectations and logistical questions.
Some candidates find this stage surprisingly candid, which is refreshing after intense technical grilling. It’s also when you get a clearer sense of the company’s culture.
Examples of Questions Candidates Report
- Technical interview questions: “Design an efficient data pipeline for streaming large-scale AI training datasets to a cluster of IPUs.”
- Algorithm challenges: “Implement a function to optimize sparse matrix multiplication with limited memory constraints.”
- Hardware-centric questions: “Explain how you would approach reducing power consumption in a multi-core AI processor without sacrificing throughput.”
- System design queries: “Outline the architecture for a scalable AI inference service that integrates with Graphcore’s software stack.”
- Behavioral questions: “Tell me about a time you had to pivot your project approach due to unexpected technical challenges.”
- Culture fit: “How do you handle situations where you disagree with senior engineers on a design decision?”
Eligibility Expectations
Graphcore tends to lean towards candidates with strong educational backgrounds, often looking for degrees in computer science, electrical engineering, physics, or related STEM fields. However, what really matters is hands-on experience with relevant technologies—like parallel computing, AI frameworks, hardware design, or systems programming.
For technical roles, 2-5 years of industry experience is generally the sweet spot, though fresh graduates with impressive research or internship projects can also make the cut. Given the complexity of their products, candidates who demonstrate problem-solving skills and adaptability often stand out more than those with purely theoretical knowledge.
Language and communication skills are essential, especially as teams are distributed across different countries and time zones.
Common Job Roles and Departments
Graphcore’s diverse portfolio calls for talent across multiple departments:
- Hardware Engineering: Focused on chip design, FPGA prototyping, and testing.
- Software Engineering: Building compilers, runtime systems, and AI frameworks optimized for IPU architectures.
- AI Research: Developing new models and algorithms that leverage the unique capabilities of Graphcore’s hardware.
- Product Management: Bridging technical teams with market needs to guide product roadmaps.
- Sales and Marketing: Technical sales engineers and strategists who communicate Graphcore's value proposition to customers.
- Operations and HR: Supporting internal processes, recruitment, and company growth.
The blend of roles means candidates come from varied backgrounds, but all share a deep interest in advancing AI technology.
Compensation and Salary Perspective
| Role | Estimated Salary |
|---|---|
| Software Engineer | £55,000 - £85,000 per year |
| Hardware Engineer | £60,000 - £90,000 per year |
| AI Research Scientist | £70,000 - £100,000 per year |
| Product Manager | £65,000 - £95,000 per year |
| Technical Sales Engineer | £50,000 - £80,000 per year + commission |
Note that these figures can vary widely based on experience, location (with London roles tending higher), and market demand. Graphcore also offers stock options and other benefits that enhance the overall package. Their compensation aligns competitively with other AI hardware firms but may be slightly below large Silicon Valley companies, reflecting their UK base and early-stage growth phase.
Interview Difficulty Analysis
Graphcore’s recruitment is often described as challenging but fair. Candidates frequently remark on the technical interviews being “intense” and requiring deep domain knowledge. Unlike generic tech interviews focusing on standard algorithms, here the questions are highly specialized, blending hardware concepts with AI software understanding.
This naturally raises the bar and can feel intimidating for those from purely software backgrounds. However, the process is transparent, and interviewers usually acknowledge if a candidate is strong overall but weaker in a niche area.
Compared to giants like Google or NVIDIA, Graphcore’s interviews are more focused on their product space rather than broad CS questions. This can be an advantage if you’ve prepared specifically for IPU systems or AI hardware design.
Preparation Strategy That Works
- Understand Graphcore’s Technology: Familiarize yourself with IPUs, dataflow architectures, and how they differ from GPUs or CPUs.
- Brush Up on Fundamentals: Strong command over algorithms, data structures, and system design is non-negotiable.
- Practice Domain-Specific Problems: Solve exercises related to parallel processing, power optimization, and AI workloads.
- Mock Interviews: Engage with peers or use platforms that simulate technical and behavioral interviews tailored to hardware/software roles.
- Prepare Questions: Demonstrate curiosity by preparing thoughtful questions about their products, research initiatives, and company culture.
- Review Your Past Work: Be ready to discuss your projects in detail, especially those involving AI, hardware, or system optimization.
Work Environment and Culture Insights
Graphcore promotes a culture of relentless innovation, emphasizing collaboration across disciplines. Interviewers often highlight the company’s startup vibe — fast-moving, experimental, and intellectually demanding. You’ll find engineers working side-by-side with researchers and product managers, fostering a cross-pollination of ideas that’s rare in larger firms.
However, this intensity can be a double-edged sword; new hires sometimes feel the pressure to quickly ramp up and contribute. But if you thrive in environments where learning is continuous and you’re empowered to take ownership, Graphcore can be incredibly rewarding.
Remote and hybrid work options are growing, but the company values in-person collaboration, especially for complex problem-solving sessions.
Career Growth and Learning Opportunities
Because Graphcore is at the intersection of AI hardware innovation, career paths are rich and varied. Engineers can transition into research roles, move into leadership, or specialize further in niche domains like compiler optimization or hardware verification.
Employees have access to cutting-edge training, conferences, and internal knowledge-sharing sessions. The company encourages curiosity-driven projects, allowing talent to explore new ideas beyond immediate deliverables.
Unlike some large corporations where roles are siloed, Graphcore’s structure enables exposure to multiple facets of AI development, accelerating professional growth.
Real Candidate Experience Patterns
Listening to candidates who recently went through the process reveals a few consistent themes. Most mention the technical interviews as the most demanding but also the most engaging part. There's a noticeable appreciation for interviewers who are not just gatekeepers but mentors—providing hints or clarifying questions to help candidates shine.
Some note that preparation materials are scarce publicly, which can be nerve-wracking. Yet, once you understand the core tech focus areas, crafting your prep becomes clearer.
On the flipside, a few candidates mention that the HR rounds can feel a bit rushed, especially for international hires. It’s advisable to be proactive about clarifying any doubts during these discussions.
Comparison With Other Employers
When stacked against other AI hardware firms like NVIDIA, AMD, or Google’s TPU team, Graphcore stands out for its niche specialization and smaller, agile team dynamics. The hiring process is somewhat less corporate and more tailored, focusing on depth rather than breadth.
While companies like NVIDIA may emphasize high-volume recruitment and standardized interview protocols, Graphcore’s approach is more selective. This can be a plus if you prefer a more personalized recruitment journey that respects your unique skills.
However, compensation and perks might lag slightly behind US tech giants, balanced by the appeal of working on the frontier of AI silicon innovation in Europe.
Expert Advice for Applicants
Focus your preparation tightly on the intersection of AI and hardware/software optimization—this is the heart of what Graphcore does. Generic coding practice won’t cut it; instead, deepen your understanding of parallel processing and machine learning workflows.
Don’t shy away from admitting gaps in knowledge during interviews. Transparency about what you know and what you are eager to learn often resonates well with interviewers.
Network within AI and hardware circles to gain insights from current or former employees. Referrals can significantly improve your chances and provide a more realistic preview of day-to-day work.
And finally, remember that the interview process is a dialogue. Prepare thoughtful questions that show you’re invested not just in the role, but in how you can contribute to Graphcore’s mission.
Frequently Asked Questions
What kind of technical skills are essential for a software engineering role at Graphcore?
Strong programming skills in C++, Python, or Rust are essential, along with a solid understanding of algorithms, system design, and parallel computing concepts. Familiarity with machine learning frameworks or compiler technologies is a significant plus.
How many interview rounds should I expect?
The typical hiring process involves around three to five rounds, including a recruiter screen, technical assessments, deep technical interviews, and a final HR interview. The exact number varies depending on the role.
Does Graphcore provide interview preparation materials?
There are no official public preparation guides, but candidates are encouraged to study AI hardware concepts, parallel programming, and system architecture. Peer forums and tech discussion groups can also be useful.
What is the typical salary range at Graphcore for engineering roles?
Engineering salaries usually range between £55,000 and £90,000 per year, depending on experience and role seniority. Stock options and bonuses can enhance total compensation.
Is remote work an option at Graphcore?
Graphcore has embraced hybrid work models post-pandemic, but the company values in-person collaboration, especially for complex projects, so some on-site presence is typically expected.
Final Perspective
Graphcore offers a compelling opportunity for those who want to be at the forefront of AI hardware innovation. Their interview process is demanding but fair, designed to surface candidates who can handle the unique challenges posed by AI silicon and software co-design.
If you’re willing to invest time in understanding their technology and preparing for domain-specific questions, you’ll find the experience rewarding. Plus, the chance to work in a collaborative, cutting-edge environment where your contributions can directly impact the future of AI is a rare career prize.
Just remember: this isn’t your run-of-the-mill tech interview. It’s a journey into an emerging field, and how you prepare, engage, and communicate your expertise will make all the difference.
graphcore Interview Questions and Answers
Updated 21 Feb 2026Research Scientist Interview Experience
Candidate: Emma T.
Experience Level: Senior
Applied Via: Conference Networking
Difficulty: Hard
Final Result:
Interview Process
5
Questions Asked
- Explain your recent research in AI accelerators.
- How do you approach publishing and collaborating in academia and industry?
- Design an experiment to benchmark a new chip architecture.
Advice
Prepare to discuss your research thoroughly and show how it applies to Graphcore's goals.
Full Experience
The interview process was extensive, including technical presentations, research discussions, and meetings with multiple teams. It was challenging but rewarding.
Product Manager Interview Experience
Candidate: David L.
Experience Level: Mid-level
Applied Via: Recruiter Outreach
Difficulty: Medium
Final Result: Rejected
Interview Process
3
Questions Asked
- How do you prioritize features in a hardware product roadmap?
- Describe a time you managed cross-functional teams.
- What do you know about AI hardware market trends?
Advice
Focus on understanding the AI hardware market and demonstrate strong leadership skills.
Full Experience
Interviews were a mix of behavioral and product strategy questions. I felt confident but lacked some specific knowledge about the AI hardware ecosystem.
Machine Learning Engineer Interview Experience
Candidate: Clara S.
Experience Level: Senior
Applied Via: Referral
Difficulty: Hard
Final Result:
Interview Process
4
Questions Asked
- Explain how you would optimize a neural network for edge devices.
- Discuss your experience with Graphcore's IPU architecture.
- Describe a project where you improved model performance significantly.
Advice
Gain a deep understanding of Graphcore's technology and be ready to discuss your ML projects in depth.
Full Experience
The process was intense, with multiple technical rounds including a whiteboard session and a presentation on a previous project. The team was very knowledgeable and collaborative.
Software Engineer Interview Experience
Candidate: Brian K.
Experience Level: Entry-level
Applied Via: Company Website
Difficulty: Medium
Final Result: Rejected
Interview Process
2
Questions Asked
- Implement a function to reverse a linked list.
- Explain multithreading concepts.
- Describe your experience with C++ or Python.
Advice
Practice coding problems and understand concurrency concepts well.
Full Experience
The coding challenge was straightforward but the technical interview focused heavily on concurrency and system design, which I was less prepared for.
Hardware Engineer Interview Experience
Candidate: Alice M.
Experience Level: Mid-level
Applied Via: LinkedIn
Difficulty: Hard
Final Result:
Interview Process
3
Questions Asked
- Explain the architecture of a modern GPU.
- How do you optimize power consumption in chip design?
- Describe a challenging hardware debugging experience.
Advice
Brush up on semiconductor fundamentals and be ready to discuss past projects in detail.
Full Experience
The interview process was rigorous with a strong focus on technical knowledge and problem-solving. The first round was a phone screen focusing on basics, followed by a technical deep dive and a final cultural fit interview.
Frequently Asked Questions in graphcore
Have a question about the hiring process, company policies, or work environment? Ask the community or browse existing questions here.
Common Interview Questions in graphcore
Q: A hare and a tortoise have a race along a circle of 100 yards diameter. The tortoise goes in one directionand the hare in the other. The hare starts after the tortoise has covered 1/5 of its distance and that too leisurely.The hare and tortoise meet when the hare has covered only 1/8 of the distance. By what factor should the hareincrease its speed so as to tie the race?
Q: Suppose a newly-born pair of rabbits, one male, one female, are put in a field. Rabbits are able to mate at the age of one month so that at the end of its second month a female can produce another pair of rabbits. Suppose that our rabbits never die and that the female always produces one new pair (one male, one female) every month from the second month on.
Q: There are two balls touching each other circumferencically. The radius of the big ball is 4 times the diameter of the small all. The outer small ball rotates in anticlockwise direction circumferencically over the bigger one at the rate of 16 rev/sec. The bigger wheel also rotates anticlockwise at N rev/sec. What is 'N' for the horizontal line from the centre of small wheel always is horizontal.
Q: There are 3 clans in an island - The Arcs who never lie, the Dons who always lie and the Slons who lie alternately with the truth. Once a tourist meets 2 guides who stress that the other is a Slon. They proceed on a tour and see a sports meet. The first guide says that the prizes have been won in the order Don, Arc, Slon. The other says that, the order is Slon, Don, Arc. (the order need not be exact). To which clan did each of the guides and the players belong? ...
Q: 36 people {a1, a2, ..., a36} meet and shake hands in a circular fashion. In other words, there are totally 36 handshakes involving the pairs, {a1, a2}, {a2, a3}, ..., {a35, a36}, {a36, a1}. Then size of the smallest set of people such that the res...
Q: T, U, V are 3 friends digging groups in fields. If T & U can complete i groove in 4 days &, U & V can complete 1 groove in 3 days & V & T can complete in 2 days. Find how many days each takes to complete 1 groove individually.
Q: ABCDE are sisters. Each of them gives 4 gifts and each receives 4 gifts No two sisters give the same combination ( e.g. if A gives 4 gifts to B then no other sisters can give four to other one.)Â (i) B gives four to A.(ii) C gives 3 to E. How much did A,B,C,E give to D?
Q: There is a room with a door (closed) and three light bulbs. Outside the room there are three switches, connected to the bulbs. You may manipulate the switches as you wish, but once you open the door you can't change them. Identify each switch with its bulb.
Q: Every day a cyclist meets a train at a particular crossing .The road is straight before the crossing and both are travelling in the same direction.Cyclist travels with a speed of 10 kmph.One day the cyclist come late by 25 minutes and meets the train 5 km before the crossing.What is the speed of the train?
Q: Tom has three boxes with fruits in his barn: one box with apples, one box with pears, and one box with both apples and pears. The boxes have labels that describe the contents, but none of these labels is on the right box. How can Tom, by taking only one p
Q: There are 7 letters A,B,C,D,E,F,GAll are assigned some numbers from 1,2 to 7.B is in the middle if arranged as per the numbers.A is greater than G same as F is less than C.G comes earlier than E.Which is the fourth letter
Q: In a Park, N persons stand on the circumference of a circle at distinct points. Each possible pair of persons, not standing next to each other, sings a two-minute song ? one pair immediately after the other. If the total time taken for singing is 28 minutes, what is N?
Q: Give two dice - one is a standard dice, the other is blank (nothing painted on any of the faces). The problem is to paint the blank dice in such a manner so that when you roll both of them together, the sum of both the faces should lie between 1 and 12. Numbers from 1-12 (both inclusive) equally likely.
Q: Raj has a jewel chest containing Rings, Pins and Ear-rings. The chest contains 26 pieces. Raj has 2 and 1/2 times as many rings as pins, and the number of pairs of earrings is 4 less than the number of rings. How many earrings does Raj have?...
Q: If I walk with 30 miles/hr i reach 1 hour before and if i walk with 20 miles/hr i reach 1 hour late. Find the distance between 2 points and the exact time of reaching destination is 11 am then find the speed with which it walks.
Q: Given a collection of points P in the plane , a 1-set is a point in P that can be separated from the rest by a line, .i.e the point lies on one side of the line while the others lie on the other side. The number of 1-sets of P is denoted by n1(P)....
Q: Consider a series in which 8 teams are participating. each team plays twice with all other teams. 4 of them will go to the semi final. How many matches should a team win, so that it will ensure that it will go to semi finals.?
Q: Jack and his wife went to a party where four other married couples were present. Every person shook hands with everyone he or she was not acquainted with. When the handshaking was over, Jack asked everyone, including his own wife, how many hands they shook?
Q: A Man is sitting in the last coach of train could not find a seat, so he starts walking to the front coach ,he walks for 5 min and reaches front coach. Not finding a seat he walks back to last coach and when he reaches there,train had completed 5 miles. what is the speed of the train ?
Q: A man driving the car at twice the speed of auto one day he was driven car for 10 min. and car is failed. he left the car and took auto to go to the office .he spent 30 min. in the auto. what will be the time take by car to go office?