TensorFlow & Chatbots 2017


Notes:

Broadly speaking, there are three main types of machine learning algorithms:

Resources:

Wikipedia:

References:

See also:

100 Best Azure Machine Learning Videos100 Best GitHub: Machine Learning100 Best Machine Learning Lecture Videos100 Best Machine Learning Tutorial Videos100 Best TensorFlow Tutorial Videos | Machine Learning & Dialog SystemsMachine Learning as a Service (MLaaS)Machine Learning Meta Guide | Sequence-to-Sequence (seq2seq) & Dialog Systems 2016


Snowbot: An empirical study of building chatbot using seq2seq model with different machine learning framework
P Guo, Y Xiang, Y Zhang, W Zhan – pdfs.semanticscholar.org
… There are a lot generic responses in the chats we have listed (Table 4, 5, 7). It’s a common problem if look at all the chatbots using seq2seq only … We built an open domain generative chatbot using seq2seq model with Tensorflow and MXNet respectively …

Understanding Human Emotions
SRB Lau, JLN Wong, P Amrutha, SL See – 2017 – oar.a-star.edu.sg
… given. This helps AngoraBot to talk to the user in a more human-like way, unlike how chatbots usually give limited and mechanical answers … follows [10] How to Make an Amazing Tensorflow Chatbot Easily. (2016, December 02) …

Alime chat: A sequence to sequence and rerank based chatbot engine
M Qiu, FL Li, S Wang, X Gao, Y Chen, W Zhao… – Proceedings of the 55th …, 2017 – aclweb.org
… Commonly used techniques for building open- domain chatbots include IR model (Ji et al., 2014; Yan et al., 2016b) and … 1https://www.tensorflow.org/tutorials/seq2seq … To further evaluate our approach, we compared it with a publicly available chatbot 2. We select 878 out of the …

Machine learning for intelligent mobile user interfaces using TensorFlow
S Mayer, HV Le, N Henze – … of the 19th International Conference on …, 2017 – dl.acm.org
… In this tutorial, we teach attendees two basic steps to run neural networks on a mobile phone: Firstly, we will teach how to develop neural network architectures and train them in TensorFlow … 2017. A New Chatbot for Customer Service on Social Media …

Machine learning with tensorflow for mobile and ubiquitous interaction
HV Le, S Mayer, N Henze – … of the 16th International Conference on …, 2017 – dl.acm.org
… Secondly, we show the process to run the trained models on a mobile phone using TensorFlow Mobile. top of page AUTHORS. Huy Viet Le Huy.Le vis.uni-stuttgart.de. Bibliometrics: publication history … 2017. A New Chatbot for Customer Service on Social Media …

Machine Learning Forensics: A New Branch Of Digital Forensics
PH Rughani, P Bhatt – International Journal of Advanced …, 2017 – search.proquest.com
… It is. based on Python and TensorFlow. The advantage of this … DeepQA also provides code to setup a Django web server. that gives the chatbot a nice graphical interface to play with … this program to train an ANN chat bot. D. Training chat bot …

A Neural Chatbot with Personality
H Nguyen, D Morales, T Chin – 2017 – stanford.edu
… 4]. For more information, see the Method section.We write our code in TensorFlow v0.12 … to quantitative results, the human test pro- vided insight into qualitative aspects of our chatbots. As subjects were deciding whether the candidate response was from the chatbot or not, many …

End-to-End Trainable Chatbot for Restaurant Recommendations
A Strigér – 2017 – diva-portal.org
… End-to-end dialog systems have shown promising performance in con- versational chatbots … The theoretical background that the chatbot implemented in this the- sis relies on is presented in this … This is the model used in this thesis to implement an end-to-end trainable chat- bot …

Mitigating the Impact of Speech Recognition Errors on Chatbot using Sequence-to-sequence Model
PJ Chen, I Hsu, YY Huang, HY Lee – arXiv preprint arXiv:1709.07862, 2017 – arxiv.org
… ing has hastened ASR failure management in modular dialog systems, ASR error handling in end-to-end chatbots is rarely … tak- ing is clearly indicated in this corpus, we can easily collect pairs of sentences as the data for our chatbot … Our algorithm is implemented in Tensorflow …

Building Chatbots from Forum Data: Model Selection Using Question Answering Metrics
M Boyanov, I Koychev, P Nakov… – arXiv preprint arXiv …, 2017 – pdfs.semanticscholar.org
… In order to train our chatbot system, we converted an entire Community Question Answering forum into a set … Our model is based on the seq2seq implementa- tion in TensorFlow … espe- cially in seq2seq models, has made it possible to quickly and directly learn chatbots from data …

Chatbot Automóvel Adaptável
TMM Ferreira – 2017 – repositorio-aberto.up.pt
… Since this chat bot is meant to be used while driving using voice to communicate, some … O advento de chatbots provou ser um digno tópico de estudo e desenvolvimento, com a … Esta dissertação tem como objetivo criar um chatbot que extenda a relação do utilizador com o seu …

Crowdtesting for chatbots: a market analysis. Empirical activity with App-Quality srl
A TRANI – 2017 – politesi.polimi.it
… Finally, looking at three main Italian sectors (Utility, Media, Bank & Insurance) we found out the existing chatbots and interacted with each and all of them to understand the progress of the actual chatbot market. Page 5. 1 Part 1 Page 6. 2 1. Company and service overview …

Emotion Recognition and History Recollection in Conversational Agents
S Freitas, J Feinglass, B Clayton – public.asu.edu
… Network Architecture: To implement the residual neural net architec- ture (ResNet) we used a combination of Tensorflow and TFLearn … While the chatbot is not making requests to a server it continues listening for requests from any program [8 … “Deep learning for Chatbots, part 2 …

Conversational Agents Embodying a Character Using Neural Networks
M Ilie, T Rebedea – rochi.utcluj.ro
… Model Description We used a slightly modified seq2seq model from Tensorflow (https://www. tensorflow.org/) … training method in different phases was the key approach that gave a major breakthrough in personality of chatbots using neural … A Neural Chatbot with Personality …

soc2seq: Social Embedding meets Conversation Model
P Bhatia, M Gavalda, A Einolghozati – arXiv preprint arXiv:1702.05512, 2017 – arxiv.org
… 2.1 Conversation Models Chatbots, also called conversational agents or dialog sys- tems, have been studied by a variety of researchers from both academia and industry … The server executes the TensorFlow graph to process every Page 5 …

How Generic Can Dialogue Breakdown Detection Be? The KTH entry to DBDC3
J Lopes – workshop.colips.org
… 100 dialogues from each chatbot were available for de- velopment purposes … This ensures that there is a similar distribution of different chatbots used in train, validation and unlabeled evaluation set … The LSTM were implemented with Tensorflow [21] using the Keras toolkit [22] …

Serving deep learning models in a serverless platform
V Ishakian, V Muthusamy, A Slominski – arXiv preprint arXiv:1710.08460, 2017 – arxiv.org
… design a serverless chatbot framework [29], Baldini et al … Tensorflow Serving [24] is the open source prediction serving sys- tem developed by Google for TensorFlow models, Velox [12] is a Berkeley research project to study personalized prediction serving with Apache Spark …

Neural Monkey: An open-source tool for sequence learning
J Helcl, J Libovický – The Prague Bulletin of Mathematical Linguistics, 2017 – degruyter.com
… other tasks including building a chatbot (Vinyals and Le, 2015), image captioning (Vinyals et al., 2015; Xu et al., 2015), or text segmentation and entity recognition (Gillick et al., 2016). Neural Monkey is an open-source toolkit written using the TensorFlow machine learning …

Intelligence on tap: artificial intelligence as a new design material
LE Holmquist – interactions, 2017 – dl.acm.org
… 7. Abadi, M. et al. Tensorflow: Large-scale machine learning on heterogeneous distributed systems … 8. Facebook scales back AI flagship after chatbots hit 70% f-AI-lure rate. The Register … 11. Vincent, J. Twitter taught Microsoft’s AI chatbot to be a racist asshole in less than a day …

Intelligence on tap: AI as a new design material
L Holmquist – Intelligence, 2017 – interactions.acm.org
… 7. Abadi, M. et al. Tensorflow: Large-scale machine learning on heterogeneous distributed systems … 8. Facebook scales back AI flagship after chatbots hit 70% f-AI-lure rate. The Register … 11. Vincent, J. Twitter taught Microsoft’s AI chatbot to be a racist asshole in less than a day …

TrumpBot: Seq2Seq with Pointer Sentinel Model
F Zivkovic, D Chen – pdfs.semanticscholar.org
… Lastly, the chatbot utilized GloVE vectors as distributed word embeddings in order to gain semantic understanding of the text [17 … From the tensorflow library, the default option available was bahdanau [1]. From class, we learned that luong [14] might be better because the weight …

Practical data science for the web professional
M Nescot – Journal of Digital & Social Media Marketing, 2017 – ingentaconnect.com
… agencies are evaluating the potential of conversational agents in the form of ‘chatbots’ to help … AI/ML: IBM Watson, Azure Machine Learning, Google Cloud ML, Tensorflow The rapidly advancing … Rather, a chatbot that can strategically bring a counsellor or other type of human …

Modeling Situations in Neural Chat Bots
S Sato, N Yoshinaga, M Toyoda… – Proceedings of ACL 2017 …, 2017 – aclweb.org
… Modeling Situations in Neural Chat Bots Shoetsu Sato The University of Tokyo shoetsu@tkl.iis.u-tokyo.ac.jp … 8https://www.tensorflow.org/ 9We randomly selected one false response candidate from the four pre-selected ones when t = 2. 123 Page 5 …

Automated Assistance in E-commerce: An Approach based on Category-Sensitive Retrieval
A Majumder, A Pande, K Vonteru, A Gangwar, S Maji… – cse.iitkgp.ac.in
… 1 Introduction To build a conversational agent and/or chatbot with sufficient artificial intelli- gence has … great importance to a wide variety of applications, starting from open-domain enter- taining chatbots which can … The LSTM used for the model was build on the Tensorflow library …

Dialogue Response Generation using Neural Networks with Attention and Background Knowledge
S Kosovan, J Lehmann, A Fischer – jens-lehmann.org
… However, there are still many open challenges when implementing the chatbots … generation methods, it’s of course also hard to include process knowledge (ie the chatbot should always ask … It is currently not implemented in TensorFlow models, so there is still work to be done …

Business Models
F Corea – … Technologies: Business Models Evolution and New …, 2017 – Springer
… you can build with TensorFlow, another company that wants to take over Google should publicly prove to provide at least what TensorFlow allows … Virtual agents and chatbots cover the low-cost side of the group, while physical world systems (eg, self-driving cars, sensors, etc …

Evaluating LSTM Networks, HMM and WFST in Malay Part-of-Speech Tagging
TP Tan, B Ranaivo-Malançon… – Journal of …, 2017 – journal.utem.edu.my
… In the modeling of sequential patterns, such as phoneme recognition [2], automatic speech recognition [3][4], speech synthesis [5], speech translation [6], chatbot and many others, RNN or the more specialized type of RNN, the long … [6] using Google’s Tensorflow framework (https …

Emotional chatting machine: emotional conversation generation with internal and external memory
H Zhou, M Huang, T Zhang, X Zhu, B Liu – arXiv preprint arXiv:1704.01074, 2017 – arxiv.org
… emotional responses in conversational chat- bots. We propose a model in the encoder-decoder framework of large-scale sequence-to-sequence arXiv:1704.01074v1 [cs.CL] 4 Apr 2017 Page 2. User: Worst day ever. I arrived late because of the traffic. Chatbot (Basic Seq2seq …

CS224N Project Final Report Bidirectional Attention Flow Model for Reading Comprehension
B Beigi, S Hemmati, M Painter – 2017 – stanford.edu
… through speech as is the case with Amazon Alexa, Google Home, etc, or text with smart answers in Google Inbox or smart replies of chatbots … The problem was that our variable scoping was not correctly used, in other words we would set up the Tensorflow nodes under a set of …

Computer-Generated Responses in Spam Email Chains
G Mittal, M Tory – Journal A2I3R, 2017 – 66.201.44.162
… Natural language processing (NLP) has been incredibly useful in solving language problems — used in chatbots, web search, etc. – Neural networks have played a major role in machine learning and … responses. Special thanks to Melanie Tory, Google TensorFlow & Compute …

A Hybrid Architecture for Multi-Party Conversational Systems
MG de Bayser, P Cavalin, R Souza, A Braz… – arXiv preprint arXiv …, 2017 – arxiv.org
… However, chat- bots coordination mechanisms is meant to regulate interactions and actions from a social perspective, whereas general … (iii) Coordinated Aware Chatbots in a … With regard to chatbot engines, there is a lack of research directed to building co- ordination laws …

Interface Conversacional para domótica
RJ da Rocha Loureiro – 2017 – repositorio-aberto.up.pt
… Chatbots as a service is growing rapidly, among developers and clients. The focus of this dis- sertation is the creation of a chatbot that will serve the users as a home assistant associated with artificial intelligence detecting behavioral patterns and giving meaningful opinions …

Ava: From Data to Insights Through Conversations.
RJL John, N Potti, JM Patel – CIDR, 2017 – pdfs.semanticscholar.org
… 3.1 Overview and Example Motivated by the arguments in Section 2, we introduce Ava, an intelligent chatbot that is aimed at … out to other machine learning platforms, by simply having the template code invoke APIs in the machine learning platform (eg TensorFlow), which can be …

Business Applications of Deep Learning
A Vieira – Ubiquitous Machine Learning and Its Applications, 2017 – books.google.com
… Google launched a recent tool SyntaxNet (code based on Tensorflow available at Github … prevent them from “inappropriate behavior”, like happened to the Microsoft Twitter chatbot, Tay Most big companies are using, testing or considering the implementation of chatbots in their …

The Conversational Business
S Etlinger – 2017 – andyblackassociates.co.uk
… 6. With chatbots, branding opportunities are tiny but potent … Converting data into a chatbot or a … “TensorFlow [an open-source library for machine intelligence] and those types of resources are great if you want to experiment with models and publish academic papers, but they don’t …

Abstractions for AI-Based User Interfaces and Systems
A Renda, H Goldstein, S Bird, C Quirk… – arXiv preprint arXiv …, 2017 – arxiv.org
… TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. (2015). http://tensorflow.org/ [2] Umut A. Acar. 2005. Self-adjusting Computation … 2016. PriBots: Conversational Privacy with Chatbots. In Symposium on Usable Privacy and Security (SOUPS) …

Utilizing bots in delivering content from Kentico Cloud and Kentico EMS
A Eikonsalo – 2017 – tampub.uta.fi
… duced. Also, the concept of a chatbot will be determined, the different ways in … Additionally, to offer some background on the technological progression of chatbots, an overview of the history of bots will be … bots. The chapter is divided to two subchapters, platforms and frameworks …

Exploring Cells and Context Approaches for RNN Based Conversational Agents
S Johnsrud, S Christensen – 2017 – brage.bibsys.no
… A conversational agent, also referred to as a chatbot, is a computer system designed to communicate with humans. Based on the input from the user, it should generate a meaningful response … What expectations we have to a chatbot, depends on its purpose …

Question Answering on the SQuAD Dataset Using Multi-Perspective Context Matching
S Fort, S Colbran – 2017 – pdfs.semanticscholar.org
… comprehension is a critical part of a large number of Natural Language Processing applications such as virtual assistants, chatbots, and information … We have implemented our models and necessary infrastructure in Python, making an extensive use of tensorflow and numpy …

DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
Y Li, H Su, X Shen, W Li, Z Cao, S Niu – arXiv preprint arXiv:1710.03957, 2017 – arxiv.org
… Developing intelligent chatbots and dialog systems is of great significance to both commercial and aca- demic … it is challenging yet appealing to build up such an intelligent chatbot which involves … All the evaluated ap- proaches are implemented by TensorFlow (Abadi et al., 2015 …

Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce
J Yu, M Qiu, J Jiang, J Huang, S Song, W Chu… – arXiv preprint arXiv …, 2017 – arxiv.org
… Last but not least, we deploy our transfer learning model for PI into our online chatbot system, which can bring in significant improvements over our existing system … Finally, we launch our new system on the chatbot platform Eva1 in our E-commerce site AliExpress2 …

Development of Deep Learning Model for Multiclass Sentiment Analysis
MA Syaekhoni, 2017 – dbpia.co.kr
(Chatbot)  – Windows 10 – Python 3.5, Tensorflow 1.1 – GTX 1080 GPU

Tweeting AI: perceptions of ai-tweeters (AIT) vs expert ai-tweeters (EAIT)
L Manikonda, C Dudley, S Kambhampati – arXiv preprint arXiv:1704.08389, 2017 – arxiv.org
… tensorflow, human 12.2% 3 Emerging trends trends, 2017, iot, machinelearning, vr, ar 11.7% 4 Applications cars, robotics, healthcare, startups, banking 11.43% 5 Lessons & learnings guide, cloud, healthcare, lessons, rstats 10.4% 6 Impact & predictions chatbots, world, impact …

Generating long and diverse responses with neural conversation models
L Shao, S Gouws, D Britz, A Goldie, B Strope… – arXiv preprint arXiv …, 2017 – arxiv.org
… augmenting the attention mechanism to include the part of the target sequence already generated, ie we include Y[0:i?2] in the arguments to the attention function: Attention(yi?1, Y[0:i?2], X). We implemented this in TensorFlow (Abadi … 3. User inputs to the Jabberwacky chatbot5 …

Neural Conversational Model with Mutual Information Ranking
H Ho, C Zhu – stanford.edu
… Chatbots, programs that simulate human beings in conversations, have been gaining traction in the tech community in … Researchers have sought out the proper configurations for a chatbot to exhibit intelligent behaviors equivalent to … https://www.tensorflow.org/tutorials/ seq2seq …

Ask Me Otherwise: Synonym-Based Memory Networks for Reading Comprehension
B Srivatsan – bharathsrivatsan.com
… learning that now powers millions of users’ interactions with their devices via Siri, Alexa, Google, and Cortana (not to mention the wave of chatbots present on platforms from Facebook to WeChat). [1] This gradual change has been …

Challenges and opportunities: from big data to knowledge in AI 2.0
Y Zhuang, F Wu, C Chen, Y Pan – Frontiers of Information Technology & …, 2017 – Springer
… Table 1 Comparison of several deep learning frameworks Framework Language Multi-GPU Speed? Applicability TensorFlow Python and C++ Yes * General … Li et al. (2016) integrated reinforcement learning with deep learning to model future reward in chatbot dialogue …

Neural Matching Models for Question Retrieval and Next Question Prediction in Conversation
L Yang, H Zamani, Y Zhang, J Guo, WB Croft – arXiv preprint arXiv …, 2017 – arxiv.org
… a critical role in many popular mobile search systems, intelligent assistants, and chat bot systems such … We used TensorFlow8 for the implementation of the neural matching models … In many question answering and chatbot/dialogue systems, new questions issued by users have …

Towards Debate Automation: a Recurrent Model for Predicting Debate Winners
P Potash, A Rumshisky – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
… Furthermore, we note that the dataset is effectively balanced, as there are 53 and 52 ex- amples with the two possible labels. We implement all our models in TensorFlow (Abadi et al., 2016). We use the LSTM cell equipped with peephole connections (Gers et al., 2002) …

Neural Response Generation with Dynamic Vocabularies
Y Wu, W Wu, D Yang, C Xu, Z Li, M Zhou – arXiv preprint arXiv:1711.11191, 2017 – arxiv.org
… We study response generation for open domain conversation in chatbots … Introduction Together with the rapid growth of social conversation data on Internet, there has been a surge of interest on build- ing chatbots for open domain conversation with data driven approaches …

Morphology dictates a robot’s ability to ground crowd-proposed language
Z Mahoor, J Felag, J Bongard – arXiv preprint arXiv:1712.05881, 2017 – arxiv.org
… The master program and chat bots store information about the users, their reinforcement and com- mands, and the simulated robots in a MySQL database … TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. Soft- ware available from tensorflow.org …

A Perspective on Natural Language Understanding Capability: An Interview with Sam Bowman
V Dhar, S Bowman – Big data, 2017 – online.liebertpub.com
… Bowman: Yeah. If you run a neural network chatbot, and chatbots by some … But this is where tools such as TensorFlow or Keras or Torch are relevant—those are the manuals that I spend my days reading in the process of really trying to build substantially new tools in NLP …

Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier
Z Wang, X Li, J Zhou – arXiv preprint arXiv:1709.03665, 2017 – arxiv.org
… 1https://www.tensorflow.org 2http://kaldi-asr.org 3https://github.com/yajiemiao/eesen 4https://github.com/baidu-research/warp-ctc … the con- text, (ii) one DNN with 3 hidden layers and 128 nodes per 5Respectively, they mean “Hi, Ali TaoBao”, “Hi, AnNa, who is a chat- bot in Alipay …

Voice conversion using Deep Learning
A Aparicio Isarn – 2017 – upcommons.upc.edu
… I specially thank the authors of Python, NumPy, TensorFlow and Keras, for the great tools they have provided me. 5 Page 7 … The new system outperforms the baseline system above in terms of naturality and similarity • The model is implemented with TensorFlow and/or Keras …

Using Natural Language Understanding
N Pathak – Artificial Intelligence for. NET: Speech, Language, and …, 2017 – Springer
… ELIZA was an interactive chat bot that could be programmed to converse with a user on any topic in English … Check out the Google Tensorflow implementation of the word2vec algorithm and Facebook’s fastText (which is based on shallow neural networks), both of which work by …

The Comparative Evaluation of Dependency Parsers in Parsing Estonian
NN Alam – pdfs.semanticscholar.org
… Language translators, chatbots, and similar software products are real-life examples where dependency parsing lies in the core of the functionality … 1 https://github.com/explosion/spaCy 2 https://nlp.stanford.edu/software/nndep.shtml 3 https://github.com/tensorflow/models/tree …

Human-Oriented IoT Solutions Using Hearable Technology from NEC
S FURUTANI, T KOSHINAKA, K OOSUGI – pdfs.semanticscholar.org
… patterns Safety management Receptor sensitivity measurement Voice?user interface (VUI) Headset/3D acoustics AI chatbot Step counts … With conventional deep learning libraries such as TensorFlow, users have to configure the neural networks themselves – something they will …

Sentence?Chain Based Seq2seq Model for Corpus Expansion
E Chung, JG Park – ETRI Journal, 2017 – Wiley Online Library
… Neural conversational models have achieved impressive results in deep learning studies. These studies provide an easy means of developing a natural language chat-bot, mainly using the seq2seq framework [21, 22]. In some cases, triple-type data schemes were adopted …

Learning to ask: Neural question generation for reading comprehension
X Du, J Shao, C Cardie – arXiv preprint arXiv:1705.00106, 2017 – arxiv.org
… Question generation systems can also be de- ployed as chatbot components (eg, asking ques- tions to start a conversation or to request feed- back (Mostafazadeh et al., 2016)) or, arguably, as a clinical tool for evaluating or improving … We implement their model in Tensorflow …

Joint Learning of Dialog Act Segmentation and Recognition in Spoken Dialog Using Neural Networks
T Zhao, T Kawahara – Proceedings of the Eighth International Joint …, 2017 – aclweb.org
… 1 Introduction Recently the burst of interactive assistants and chatbots leads to an increasing interest of dialog systems … Table 4 demonstrates the calculation of DSER and DER. 1https://www.tensorflow.org/ 2https://taku910.github.io/crfpp/ 708 Page 6 …

Predicting Users’ Negative Feedbacks in Multi-Turn Human-Computer Dialogues
X Wang, J Wang, Y Liu, X Wang, Z Wang… – Proceedings of the Eighth …, 2017 – aclweb.org
… 4.3 Experimental Settings All the neural network models are implemented with TensorFlow toolkit3. The max length of the input sentence is set to 10 and all sentences are padded to the max length with zero vectors … 3www.tensorflow.org/ input of a SVM classifier …

Will productivity growth return in the new digital era? An analysis of the potential impact on productivity of the fourth industrial revolution
I Saniee, S Kamat, S Prakash… – Bell Labs Technical …, 2017 – ieeexplore.ieee.org
… apparent. Last, the rise of AI systems, in the form of image and voice recognition and chatbots has an undeniable future trajectory that will transform communication between people, things, systems and platforms. We therefore …

Evaluating Generative Models for Text Generation
P Kawthekar, R Rewari, S Bhooshan – pdfs.semanticscholar.org
… 1 Introduction Being able to generate text that is close to the quality of human generated text has a lot of applications like translation from one language to another, chatbots, question answering etc … arXiv preprint arXiv:1609.05473 (2016). [5] https://www.tensorflow.org/tutorials …

Data management in machine learning: Challenges, techniques, and systems
A Kumar, M Boehm, J Yang – Proceedings of the 2017 ACM International …, 2017 – dl.acm.org
… Ava [53] provides a chat-bot front-end to make it easier to … [3] Oracle R Enterprise. www.oracle.com/technetwork/ database/database-technologies/r/r-enterprise. [4] M. Abadi et al. TensorFlow: A System for Large-Scale Machine Learning. OSDI, 2016. [5] D. Agrawal et al …

Towards the Implementation of an Intelligent Software Agent for the Elderly
AHF Dinevari – 2017 – era.library.ualberta.ca
… foundation of Artificial Intelligence. Chatterbots are also known as chatbots and artificial conversational entities … terbots. Ontologies are sometimes referred to as Semantic Networks by some chatbot systems. • AIML is a method of defining patterns in chatterbots. It is written in …

A berkeley view of systems challenges for ai
I Stoica, D Song, RA Popa, D Patterson… – arXiv preprint arXiv …, 2017 – arxiv.org
… inaccurate labels. For example, the Microso Tay chatbot relied heavily on human interaction to develop rich natural dialogue capabilities. However, when exposed to Twi er messages, Tay quickly took on a dark personality [16]. In …

PacGAN: The power of two samples in generative adversarial networks
Z Lin, A Khetan, G Fanti, S Oh – arXiv preprint arXiv:1712.04086, 2017 – arxiv.org
… (eg frame prediction [45], image super-resolution [25], and image-to-image translation [17]), as well as dialogue systems or chatbots—applications where … like architecture for these exper- iments, which is based on the code at https://github.com/carpedm20/DCGAN-tensorflow …

Grounding Referring Expressions in Images by Variational Context
H Zhang, Y Niu, SF Chang – arXiv preprint arXiv:1712.01892, 2017 – arxiv.org
… natural language in visual data is a hallmark of AI, since it establishes a communication channel between humans, machines, and the physical world, underpinning a variety of multimodal AI tasks such as robotic naviga- tion [35], visual Q&A [1], and visual chatbot [6]. Thanks to …

Rozpoznávání pojmenovaných entit s pomocí rekurentních neuronových sítí
HL Nguyen – 2017 – dspace.cvut.cz
… 3. Implement the neural network in Tensorflow for sequence labelling … With the increase of chatbots, personal assistants and AI conversation agents, the need for good natural language processing (NLP) and natural lan- guage understanding (NLU) systems increases …

The Executive Guide to Artificial Intelligence: How to identify and implement applications for AI in your organization
A Burgess – 2017 – books.google.com
… Interestingly, even now, this same approach is being used in many of the chatbots that have proliferated across the internet. Most of these claim to use AI, and some do, but most are passive decision trees. There are a number of online chatbot platforms (most are free to use …

The current state of fake news: challenges and opportunities
Á Figueira, L Oliveira – Procedia Computer Science, 2017 – Elsevier
… Content-creation: Each time a user posts/shares content, the system uses a created “chat bot” to determine if the new post contains any … For instance, Google has provided the use of part of its proprietary Deep Learning TensorFlow AI for free to its commercial customers …

Artificial Intelligence and Exponential Technologies: Business Models Evolution and New Investment Opportunities
F Corea – 2017 – books.google.com
Page 1. SPRINGER BRIEFS IN APPLIED SCIENCES AND TECHNOLOGY ? COMPUTATIONAL INTELLIGENCE Francesco Corea Artificial Intelligence and Exponential Technologies: Business Models Evolution and New Investment Opportunities 123 Page 2 …

A retail conversational interface to naturally capture unstructured information triggering high value analytical and operational business actions
RM da Silva Gomes – 2017 – repositorio-aberto.up.pt
… ” [Reh]. Some of the common uses of NLP are deep analytics, summarizing blocks of text, creation of chat bots, identifying types of entities, identifying the sentiment of a given string of text or automatically translating text from one human language to another …

Analysis of the Supreme Court’s arguments using natural language processing techniques
L Polák – 2017 – dspace.cvut.cz
… Among the datasets with exotic structures, there is a group of datasets – discussions forums, chat bots, messengers or dialogues – that share common traits. All of them require a different type of analysis – Discourse Analysis …

In (Cyber) Space Bots Can Hear You Speak: Breaking Audio CAPTCHAs Using OTS Speech Recognition
S Solanki, G Krishnan, V Sampath… – Proceedings of the 10th …, 2017 – dl.acm.org
Page 1. In (Cyber)Space Bots Can Hear You Speak: Breaking Audio CAPTCHAs Using OTS Speech Recognition Saumya Solanki University of Illinois at Chicago ssolan5@uic.edu Gautam Krishnan University of Illinois at Chicago gkrish3@uic.edu …

Deep Active Learning for Short-Text Classification
W Zhao – 2017 – diva-portal.org
… 1 Page 8. 2 CHAPTER 1. INTRODUCTION Currently, text classification is one of the key problems of most artificial intelligence companies, which aim to build up chat bot systems or intelligent custom service sys- tems. Recurrent …

How Copyright Law Can Fix Artificial Intelligence’s Implicit Bias Problem
A Levendowski – 2017 – papers.ssrn.com
Page 1. HOW COPYRIGHT LAW CAN FIX ARTIFICIAL INTELLIGENCE’S IMPLICITBIAS PROBLEM Amanda Levendowski* ABSTRACT As the use of artificial intelligence (AI) continues to spread, we have seen an increase in …

Modular Learning Component Attacks: Today’s Reality, Tomorrow’s Challenge
X Zhang, Y Ji, T Wang – arXiv preprint arXiv:1708.07807, 2017 – arxiv.org
… The results are summarized in Figure 2. It is shown that Word2Vec is employed as a basic building block in a variety of projects ranging from general-purpose ML libraries to domain- specific applications (eg, Chatbot). Similar …

Artificial Intelligence for .NET: Speech, Language, and Search
N Pathak – Springer
Page 1. Artificial Intelligence for .NET: Speech, Language, and Search Building Smart Applications with Microsoft Cognitive Services APIs — Nishith Pathak Page 2. Artificial Intelligence for .NET: Speech, Language, and Search Building Smart Applications with Microsoft …

Speeding Up Ab-Initio Molecular Dynamics With Artificial Neural Networks
HV Treider – 2017 – duo.uio.no
… The potential is pre-trained using TensorFlow, a powerful machine learning library from Google, on atomic configurations computed with classical potentials … 114 9 Our Scientific Toolbox 117 9.1 TensorFlow …

Neural Logic Framework for Digital Assistants
N Cingillioglu, A Russo, K Broda – 2017 – imperial.ac.uk
… 38 3.4 Continuous bag-of-words and skip-gram models presented in word2vec [1]. . 39 3.5 Word2vec results from TensorFlow [2] example implementation. . . . . 41 3.6 Superlative linear structures in learnt vectors from GloVe. . . . . 42 …

Artificial Intelligence in Life Extension: from Deep Learning to Superintelligence
M Batin, A Turchin, S Markov, A Zhila… – …, 2017 – search.proquest.com
… [83] are using a multilayer neural network to predict the electrical properties of new molecules; – L. Rampasek and A. Goldenberg [84] are reviewing applications of neural-network project TensorFlow by Google in computational biology; … AI chatbots, such as the Babylon app [5]; …

Schedule Highlights
P Sturm – Machine Learning, 2017 – pdfs.semanticscholar.org
Page 1. NIPS 2017 Workshop book Generated Tue Nov 07, 2017 Page 1 of 42 Workshop organizers make last-minute changes to their schedule. Download this document again to get the lastest changes, or use the NIPS mobile application. Schedule Highlights Dec. 8, 2017 …

Artificial Intelligence in Life Extension: from Deep Learning to Superintelligence
A Turchin, D David, Z Alice, M Sergey, B Mikhail – 2017 – philpapers.org
… [83] are using a multilayer neural network to predict the electrical properties of new molecules; – L. Rampasek and A. Goldenberg [84] are reviewing applications of neural-network project TensorFlow by Google in computational biology; … AI chatbots, such as the Babylon app [5]; …

A Survey on Resilient Machine Learning
A Kumar, S Mehta – arXiv preprint arXiv:1707.03184, 2017 – arxiv.org
… Microsoft’s twitter chatbot Tay started tweeting racist and sexist tweets in less than 24 hours after it was opened to public for learning [3]. This survey categorizes major works in Adversarial Machine Learning area in three broad categories. First set consists of Page 2 …

Workshop Program
A ANANDKUMAR, FEI SHA – 2017 – pdfs.semanticscholar.org
Page 1. THE 34TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING ICML @ SYDNEY INTERNATIONAL CONFERENCE ON MACHINE LEARNING ANIMA ANANDKUMAR FEI SHA Thu Aug 10th – Fri Aug 11th WORKSHOP PROGRAM WORKSHOP CHAIRS …

Design and development of a cognitive assistant for the architecting of earth observing satellites
A Virós Martin – 2017 – upcommons.upc.edu
Page 1. DDC AAE OS by Antoni Virós Martin September 2017 Submitted to the faculty of the Barcelona School of Informatics (FIB) of Universitat Politècnica de Catalunya (UPC) – BarcelonaTech in Partial Fulfillment of the Requirements for the …

Building AI Applications: Yesterday, Today, and Tomorrow.
RG Smith, J Eckroth – AI Magazine, 2017 – pdfs.semanticscholar.org
… TensorFlow (Google) Machine learning toolkit OpenCV (itseez) Computer vision library Sphinx (CMU) Speech recognition toolkit Drools (Red Hat) Rule-driven expert system shell, planning engine GATE (University of Sheffield) Natural language processing toolkit Robot …

Artificial Intelligence and the Future of Defense: Strategic Implications For Small-and Medium-Sized Force Providers
S De Spiegeleire, M Maas, T Sweijs – 2017 – books.google.com
Page 1. ARTIFICIAL INTELLIGENCE AND THE FUTURE OF DEFENSE STRATEGIC IMPLICATIONS FOR SMALL- AND MEDIUM-SIZED FORCE PROVIDERS The Hague Centre for Strategic Studies SECURITY Page 2. HCSS …

The Practical Concepts of Machine Learning
P Kashyap – Machine Learning for Decision Makers, 2017 – Springer
… They are coming up with the chatbot (automated user query replying machines/software) type of products/service by leveraging already … learning, some of them being emotion based products and services, intuitive learning, intelligent drones and robots, chatbots, and many more …

Can Robots Be Lawyers: Computers, Lawyers, and the Practice of Law
D Remus, F Levy – Geo. J. Legal Ethics, 2017 – HeinOnline
… See Vector Representations of Words, TENSORFLOw, https:// www.tensorflow.org/versions/ rO.11/tutorials/word2vec/index.html [https://perma.cc/KH96-WYVZ] (last up- dated Dec. 20, 2016). We focus on LSA here because the logic is more intuitive. 27 …

Why the Dynamics of Competition for Online Platforms Leads to Sleepless Nights But Not Sleepy Monopolies
DS Evans – 2017 – papers.ssrn.com
Page 1. 1 WHY THE DYNAMICS OF COMPETITION FOR ONLINE PLATFORMS LEADS TO SLEEPLESS NIGHTS, BUT NOT SLEEPY MONOPOLIES David S. Evans* August 23, 2017 Revision of July 25, 2017 Draft Abstract …

Zen of Facticity: Bull, Ox or Otherwise?
A Judge – 2017 – laetusinpraesens.org
Herding facts and their alternatives in a post-truth-era.

Visually grounded interaction and language
F Strub, H de Vries, A Das, S Kottur… – Schedule …, 2017 – pdfs.semanticscholar.org
Page 29. NIPS 2017 Workshop book Generated Tue Nov 21, 2017 Page 29 of 58 perspectives, identify ways to bridge theory and practice, and discuss avenues of future research. Schedule 09: 00 AM Intro/Survey of Nearest …

Data Efficient Deep Reinforcement Learning through Model-Based Intrinsic Motivation
MS Nylend – 2017 – brage.bibsys.no
… 2006), recommendation systems (Shani et al. 2012), advertising (Cai et al. 2017), dynamic pricing (Raju et al. 2003), chatbots (Li et al. 2016) and power optimization2. 1.1 Motivation All the mentioned RL problems have one thing in common, which is that they need very …

SingularityNET: A decentralized, open market and inter-network for AIs
B Goertzel, S Giacomelli, D Hanson, C Pennachin… – 2017 – icotokn.com
… open-source AI tools. Among many other options, for instance, we have been exploring possibilities such as • Neural net tools such as Caffe, Keras, Gluon, Tensorflow, Mxnet, DL4J and others; • generic machine learning toolkits …

Development Of Machine Intelligence–Karnataka Action Plan
KJA RECOMMENDATION – 2017 – karnataka.gov.in
Page 1. DEVELOPMENT OF MACHINE INTELLIGENCE – KARNATAKA ACTION PLAN PREPARED BY KJA TASK GROUP KJA RECOMMENDATION Karnataka Jnana Aayoga (Karnataka Knowledge Commission) Government of Karnataka September 2017 …

A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade
R Buyya, SN Srirama, G Casale, R Calheiros… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade Rajkumar Buyya?1, Satish Narayana Srirama†2,1, Giuliano Casale3, Rodrigo Calheiros4, Yogesh Simmhan5, Blesson …

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