Bandung, bharindojakartaindonesia – Pelaksanan kegiatan Press Ghatering Dinas Kominfo Kabupaten Belitung dan 50 Perwakilan Wartawan Belitung memasuki hari kedua, sesuai dengan rencana yang telah disusun akan melakukan kunjungan ke media Pikiran Rakyat dan PT. Promedia Teknologi Indonesia.
Kedatangan rombongan dari Kabupaten Belitung yang dipimpin langsung Kepala Dinas Kominfo Mohammad Iqbal, ST, sambut hangat dari tuan rumah media Pikiran Rakyat membuat suasana menjadi lebih hidup.
Pada saat kunjungan ini juga dihadiri oleh Anggota Komisi 1 DPRD Belitung Wahyu Affandi, Kepala Bappeda Belitung H. Nurman Sunanda, SE MM, Kepala Dinas PUPR Kabupaten Belitung Edi Usdianto ST, Kabid beserta staf Kominfo, staf Prokopim Setda Pemkab Belitung dan para insan pers yang mengikuti Press Ghatering.
Saat memberikan kata sambutannya Hazmirullah Pimpinan Redaksi Pikiran Rakyat (Pimpred) di dampingi Satrya Graha laksana yang sebagai penanggung jawab media online Pikiran Rakyat dan masing-masing Devisinya, menjelaskan sejarah berdirinya Media Pikiran Rakyat di Bandung.
“Pikiran Rakyat bermula dari Surat Kabar, namanya sudah ada di tahun 50an kerap kali dikaitkan dengan buletin diterbitkan oleh Soekarno. Sesungguhnya bukan tidak berkaitan, tapi sudah beberapa kali ganti pengurus dan ulang tahun kami pada 24 Maret tahun 1966,” jelas Hazmirullah yang juga pernah didaulat menjadi wisudawan terbaik Program Doktoral di Universitas Padjadjaran.
Menurutnya, Kami juga beradaptasi dengan teknologi dan semenjak 2006 kami merintis pikiranrakyat.com , koran harus lebih dalam menceritakan sesuatu peristiwa. Sampai saat ini sebenarnya bisnis online belum menemukan bentuk yang mapan, maka ada yang sifatnya cooperate, ada yang sindikasi dan Pikiran Rakyat saat ini memilih yang lebih nyaman yaitu kemitraan.
” Terkait dengan pemerintahan teman pers itu, hanya memposisikan diri sebagai kontrol sosial. Jadi seolah-olah Pemda itu harus saling serang, padahal itu hanya salah satu fungsi yang tercantum dalam UU Pers No. 40 Tahun 1999. Adapun fungsi yang pertama itu edukasi, apa program-program atau kebijakan yang diterbitkan pemerintah itu menjadi bahan edukasi. Dan pemerintah mungkin ada keterbatasan terkait sosialisasi dan publikasinya, maka semua bisa dimanfaatkan untuk di sosialisasikan dan dipublikasikan secara luas melalui media yang ditargetkan pemerintah,” ujar Hazmir yang juga berasal dari Palembang ini.
Konsep edukasi ini menjadi penting, karena pemerintah juga berkepentingan semua kebijakan dan regulasi dapat bisa tersosialisasikan. Jadi fungsi itu yang kami jalankan selama ini selain kontrol sosial dan penyebaran informasi secara umum.
“Kami Pikiran Rakyat menjalin kerjasama yang cukup erat dengan DPRD Provinsi dan DPRD Kabupaten, untuk tahun ini dari DPRD Provinsi bahkan dalam sebulan ada seratus berita yang kami liput terkait dengan Pimpinan DPRD dan anggota dewan beserta kelengkapan dewannya. Demikian juga dengan pemeritah kota dan Kabupaten,” paparnya.
Sementara itu Kepala Dinas Kominfo Kabupaten Belitung M Iqbal dalam sambutannya, mengatakan bahwa kunjungan rombongan dari Belitung dalam rangka silahturahmi dan mendapatkan ilmu serta menggali lebih banyak bagaimana sinergi pemerintah daerah dengan insan pers juga masyarakat.
” Terus terang Kabupaten Belitung sebelumnya adalah daerah tambang beralih ke pariwisata, kita ketahui bahwa tulisan jurnalis bisa membuat pariwisata ambruk dan bisa berkembang. Namun dengan promosi atau tulisan kawan-kawan pers, bisa maju atau juga bernilai negatif,” jelas Iqbal.
Fungsi kawan-kawan ini sangat besar sekali, kami juga ingin mendapatkan pengalaman dari Pikiran Rakyat bagaimana membangun sinergi itu dalam membangunan juga membranding Belitung. Supaya bisa berkembang untuk pariwisatanya, kami perlu informasi dan pengalaman -pengalamannya.
“Dan sehingga jurnalis Belitung bisa menambah wawasan dan mungkin berbagi pengalaman , bagaimana kawan-kawan jurnalis bekerja di Belitung. Media ini selain edukasi juga menjadi sarana Promosi disiminasi informasi,” ujar Iqbal.
Dalam kunjungan ke Pikiran Rakyat ini, banyak informasi dan wawasan yang di dapat perihal bagaimana untuk membangun hubungan dengan pemerintah. Apalagi di era digital yang persaingan dan tantangan sangat ketat, dengan banyaknya surat kabar sudah mulai tergerus dengan perkembangan zaman. Pihak Pikiran Rakyat menjelaskan strategi serta cara mengelola untuk menghadapi keinginan atau pangsa pasar di Media online.
Kegiatan selanjunya rombongan Press Ghatering Dinas Kominfo Kabupaten Belitung, dihari yang sama berkunjung ke PT . Promedia Teknologi Indonesia. Dalam kunjungan tersebut, para jutnalis, kominfo dan staf Prokopim Setda Belitung mendapatkan informasi dan cara bermitra dengan PT . Promedia Teknologi Indonesia.(TIM)
Jumat, (10/11/2023), Bharindo, Banjarnegara — Rumah Tahanan Negara (Rutan) Kelas IIB Banjarnegara gandeng Kodim (0704) Banjarnegara dan Polres Banjarnegara untuk bersinergi dalam rangka melaksanakan penggeledahan kamar hunian dan tes urine bagi Warga Binaan Kamis, (9/11/2023) kemarin. Penggeledahan seluruh kamar hunian dan tes urine bagi warga binaan ini adalah komitmen Rutan Banjarnegara melakukan deteksi dini dalam upaya menjaga keamanan dan ketertiban menjelang pesta demokrasi di tahun 2024 dan untuk menciptakan suasana yang kondusif diakhir tahun 2023.
Selain bertujuan untuk mensukseskan Pemilu 2024 dan menjaga kondusifitas ketika pergantian tahun, kegiatan ini juga merupakan bentuk upaya dari Rutan Banjarnegara ikut andil dalam mewujudkan Rencana Aksi Nasional P4GN (Pencegahan dan Pemberantasan Penyalahgunaan dan Peredaran Gelap Narkotika dan Prekusor Narkotika).
Dalam sambutannya, Karutan Banjarnegara, Bima Ganesha Widyadarma menyampaikan terima kasih kepada Kodim 0704 dan Polres Banjarnegara serta Pegawai Rutan Banjarnegara.
Menurut Bima, “Giat ini sebagai bentuk kontribusi Rutan dalam mensukseskan pemilu tahun 2024 dan implementasi dari 3 kunci pemasyarakatan maju yaitu deteksi dini, berantas narkoba, dan sinergritas dengan aparat penegak hukum serta back to basic, yang mana apabila ditemukan barang terlarang maka akan kami tindak lanjuti sesuai dengan arahan atasan kantor wilayah,” ucap Bima.
“Untuk kita pedomani, dalam melakukan penggeledahan kamar dan tes urine warga binaan pemasyarakatan (WBP) ini, kita harus tetap menjaga etika dan tunjukan sikap yang humanis,” pesan Bima.
Dalam kesempatan yang sama Ka. KPR, Suparno menyampaikan, “Kegiatan penggeledahan dan tes urine ini juga bertujuan untuk menjaga kondusifitas di dalam Rutan.
Petugas dibagi kedalam 4 kelompok yang masing-masing didampingi oleh anggota TNI dan POLRI. Untuk TNI menjaga Ring 2 (Sekeliling Kamar Hunian WBP) dan Polri mengawasi Ring 1 (Teras Halaman Blok Hunian),” ujar Suparno.
“Untuk jumlah penghuni/WBP di Rutan Banjarnegara saat ini 116 orang. Selama Kegiatan WBP bersikap kooperatif baik dalam razia maupun tes urine.
Release dalam giat ini didapatkan barang seperti paku, balok kayu, korek api, kancing dan benang serta nol narkoba,” ucap Parno. “Barang-barang temuan ini selanjutnya akan kami musnahkan dengan mempertimbangkan arahan pimpinan,” sambungnya.
“Hasil dari kegiatan razia gabungan aparat penegak hukum ini akan menjadi laporan kepada pimpinan dan untuk evaluasi guna menciptakan suasana Rutan yang kondusif, lebih aman dan bebas dari penyalahgunaan/peredaran narkotika serta benda-benda terlarang lainnya,” pungkas Suparno. (ugl/hms/awi)
Senin, (30 Oktober 2023) Bharindo, Beijing – Wakil Menteri Pertahanan RI M. Herindra, mengajak negara-negara di berbagai belahan dunia untuk bersatu dalam kerja sama yang kolaboratif guna menangani berbagai persoalan keamanan global yang berpotensi semakin memanas.
Seruan tersebut disampaikan Wamenhan saat secara langsung membacakan naskah pidato dari Menhan RI, Prabowo Subianto, dalam the first plenary session di Xiangshan Forum pada Senin, (30/10/23). Menhan Prabowo sendiri berhalangan hadir karena tugas-tugas kenegaraan.
“Pertama-tama, izinkan saya menyampaikan permintaan maaf dari Bapak Menhan kami, Pak Prabowo Subianto, karena tidak bisa hadir secara langsung hari ini, karena Beliau memiliki tugas-tugas kenegaraan yang tidak dapat ditinggalkan,” ujar Wamenhan M. Herindra saat mengawali pidatonya.
Turut hadir menjadi pembicara pada the first plenary session ini adalah Menhan Rusia, Deputy Prime Minister of Cambodia, Kepala Staf Gabungan Angkatan Bersenjata Brazil, Sekjen ASEAN, dan Deputy Sekjen Shanghai Cooperatioan Organization.
Melanjutkan pembacaan naskah pidato tersebut, Wamenhan berkata: “Masing-masing dari kita mempunyai tugas bersama untuk saling mendukung, terutama ketika masa-masa sulit.
Di saat menghadapi tantangan atau kesulitan, prinsip persatuan dan kolaborasi akan menghantar kita pada perbedaan dalam melihat sebuah masalah atau konflik.
Ketika kita bersatu, kita menciptakan lingkungan yang mendukung dan penuh harapan, yang memungkinkan kemajuan dan memastikan suasana damai,” demikian Wamenhan.
“Di dunia yang saling terhubung saat ini, tidak ada negara yang bisa berjalan sendiri.
Tantangan – seperti ancaman dunia maya, sengketa wilayah, dan krisis kesehatan global – berdampak pada kita semua dan tidak melihat lagi batas negara.
Untuk mengatasi permasalahan ini, kolaborasi dan upaya kolektif sangatlah penting.
Bahkan negara terkuat sekalipun tidak dapat mengatasi permasalahan ini sendirian,” ujar Wamenhan.
Wamenhan menguraikan bahwa negara-negara besar dan kuat secara militer, ekonomi, dan diplomasi, akan sangat mempengaruhi panggung pergerakan dunia; namun hal ini tidak berarti bahwa negara-negara yang berkembang tidak memiliki kontribusi yang besar pada pergerakan roda dunia; sebaliknya, kolaborasi dari berbagai skala kekuatan negara-negara ini harus berjalan selaras dengan prinsip-prinisp Hukum Internasional yang menghargai semangat kedaulatan dan independensi.
Turut hadir juga dalam event ini adalah Menteri Pertahanan dari sejumlah negara, termasuk Papua New Guinea, Nigeria, Singapura dan lainnya. Selanjutnya, Wamenhan mengajak negara-negara di dunia untuk memformulasikan sebuah kolaborasi ekonomi guna menciptakan keberhasilan jejaring rantai pasok dunia. Hal ini akan menciptakan “interdependensi antarnegara yang kelak akan menjadi solusi bagi perang dagang dan konflik berbasis ekonomi.”
“Dengan terciptanya mekanisme kerja sama ekonomi yang kolaboratif ini, niscaya kita tengah mewujudkan stabilitas keamanan regional dan global,” ujar Wamenhan.
“Sebagai penutup, kami menyerukan kepada semua negara, terutama negara-negara yang memiliki pengaruh signifikan, untuk menjunjung dan memperjuangkan nilai-nilai ini. Hanya dengan bekerja sama, kita dapat mewujudkan visi dunia yang damai dan kooperatif. Masing-masing dari kita mempunyai peran dalam membangun masa depan yang harmonis dan aman,” demikian Wamenhan M. Herindra saat mengakhiri pidatonya.
Senin, (30 Oktober 2023) Bharindo, Banyumas – Bantuan Kementerian Pertahanan dan Unhan atasi solusi kekeringan di Jawa Tengah, di apreasiasi para warga dan Kepala Desa di lima wilayah Jawa Tengah.
Para Kepala Desa di lima wilayah di Jawa Tengah mengungkapkan sangat merasakan manfaat bantuan yang diberikan Menhan Prabowo.
“Beribu terima kasih, betul-betul solusi. Ini betul nyata untuk mengatasi kekeringan warga,” kata Kepala Desa Karang Kemojing.
“Ini menjadi motivasi kita untuk ke depan dan mudah-mudahan bantuan ini nggak hanya hari ini, bisa ditambahkan lagi,” sambungnya.
Saat virtual zoom dengan Menhan Prabowo bersama Rektor Universitas Pertahanan (Unhan) Mayjen TNI Jonni Mahroza dan Dekan Fakultas Logistik Militer Laksma TNI Agus di Desa Suro, Banyuwangi, Minggu, (29/10/23) kemarin. Kepala Desa Kali Agung, Purworejo mengungkapkan rasa terima kasih sekaligus menangis haru, karena sebelumnya di desanya terdapat 5 dusun yang sangat kekeringan air. Saat ini, sudah 170 KK atau 600 jiwa yang bisa menikmati sumber air bersih.
Sementara itu, Kepala Desa Ngaren, Boyolali mengucapkan syukur atas bantuan sumur bor oleh Menhan Prabowo, karena empat dusun yang sebelumnya mengalami kendala air bersih, kini sudah mendapatkan air dengan mudah.
“Nanti saya mohon kepada Pak Pabowo, ada satu titik lagi desa yang berbatasan dengan antardusun lainnya,” ujarnya.
Menanggapi hal tersebut, Menhan Prabowo mengungkapkan rasa bahagia atas manfaat yang dirasakan masyarakat.
“Insha Allah, kita bisa teruskan, tentunya sesuai dengan kemampuan. Saya titip, tolong dijaga,” kata Prabowo.
Intercom vs Zendesk: Comparing features, integrations, and pricing
In 2023, conversational messaging will play an essential role in customer service. Customers increasingly expect to receive fast, convenient, and personalized support. No matter how a customer contacts your business, your agents will have access to the tools and information they need to continue and close conversations on any channel. Intercom wins the sales pipeline tools category because its campaigning and sequencing tools integrate all channels and unique services, like carousels and product tours.
Zendesk Suite 2023 Pricing, Features, Reviews & Alternatives – GetApp
Zendesk Suite 2023 Pricing, Features, Reviews & Alternatives.
Resolve complex issues more efficiently with tickets designed to keep the conversation going. Intercom is human-powered and AI-enhanced, helping you deliver personalized, conversational support that scales with your business. Intercom is fully integrated, omnichannel, and easy to use—so you can deliver quality, conversational support from start to finish. However, if you’re looking for a streamlined, all-in-one messaging platform, there is no better option than Messagely. Chat agents also get a comprehensive look at their entire customer’s journey, so they will have a better idea of what your customers need, without needing to ask many questions. Since Intercom doesn’t offer a CRM, its pricing is divided into basic messaging and messaging with automations.
Smooth migration. Simple integration.
Intercom allows visitors to search for and view articles from the messenger widget. Customers won’t need to leave your app or website to find the help they need.Zendesk, on the other hand, will redirect the customer to a new web page. With both tools, you can also use support bots to automatically suggest specific articles, track customers’ ratings, and localize help center content to serve your customers in their native language. Intercom does not offer a native call center tool, so it cannot handle calls through a cloud-based phone system or calling app on its own.
Design and send out mobile push messages–phone pop-ups containing text and images that prompt customers to take action and redirect to a specific app page when clicked. Zendesk for Sales, or Zendesk Sell, is Zendesk’s sales pipeline and CRM tool with its own dashboard for lead generation and conversion. With so many solutions to choose from, finding the right option for your business can feel like an uphill battle.
Best 10 Zoho Desk Alternative Tools for Support Teams in 2023
Besides, the prices differ depending on the company’s size and specific needs. We conducted a little study of our own and found that all Intercom users share different amounts of money they pay for the plans, which can reach over $1000/mo. The price levels can even be much higher if we’re talking of a larger company. So yeah, all the features talk actually brings us to the most sacred question — the question of pricing. You’d probably want to know how much it costs to get each of the platforms for your business, so let’s talk money now.
How Is AI Impacting The SaaS Landscape with a16z GP Kristina Shen – saastr.com
How Is AI Impacting The SaaS Landscape with a16z GP Kristina Shen.
So if an agent needs to switch from chat to phone to email (or vice versa) with a customer, it’s all on the same ticketing page. There’s even on-the-spot translation built right in, which is extremely helpful. Leave your email below and a member of our team will personally get in touch to show you how Fullview can help you solve support tickets in half the time. If you are looking for a comprehensive customer support solution with a wide range of features, Zendesk is a good option. Both Zendesk and Intercom offer varying flavors when it comes to curating the whole customer support experience. In terms of G2 ratings, Zendesk and Intercom are both well-rated platforms.
Zendesk is a great option for large companies or companies that are looking for a very strong sales and customer service platform. It offers more support features and includes more advanced analytics and reports. On the other hand, Zendesk’s customer support includes a knowledge base that’s very intuitive and easy to navigate. It divides all articles into a few main topics so you can quickly find the one you’re looking for. It also includes a list of common questions you can browse through at the bottom of the knowledge base home page so you can find answers to common issues.
How to Use Retail Bots for Sales and Customer Service
Ever wonder how you’ll see products listed on secondary markets like eBay before the products even go on sale? Sometimes instead of creating new accounts from scratch, bad actors use bots to access other shopper’s accounts. Block them completely, let some shop, or even send them to a fake site to distract them and give humans a chance to purchase the goods as the retailer intended.
For instance, it offers personalized product suggestions and pinpoints the location of items in a store. The app also allows businesses to offer 24/7 automated customer support. The usefulness of an online purchase bot depends on the user’s needs and goals.
How to identify an ecommerce bot problem
This way, each shopper visiting your eCommerce website will receive personalized product recommendations. Consequently, your customers will not encounter any friction when shopping with you. Modern consumers consider ‘shopping’ to be a more immersive experience than simply purchasing a product. Customers do not purchase products based on their specifications but rather on their needs and experiences. H&M, another fashion retailer, also successfully applies chatbots for the business. H&M Facebook Messenger chatbot recommends goods on the basis of customer preferences.
Starting as a simple paraphrasing tool, Quillbot has become a robust AI writing assistant that symbolizes a significant stride in AI content optimization. This review thoroughly explores Quillbot AI, focusing on its key features, pricing structure, and strengths and weaknesses. It also comes with exit intent detection to reduce page abandonments. A tedious checkout process is counterintuitive and may contribute to high cart abandonment. Across all industries, the cart abandonment rate hovers at about 70%.
‘Uber Was Supposed to Help Traffic. It Didn’t. Robotaxis Will Be … – Slashdot
SnapTravel is a great option for those who are looking to spend as little time organizing their trip as possible. All you have to do is enter the details of your trip, and the bot will find the best match and deal. You can either go to their website or download their bot to one of the given messaging apps. He once scored eight pairs of Adidas Yeezy sneakers (each costing around US$200) and managed to resell each one for between US$500 to US$600. But increasing demand and fledgling supply weren’t the only things that spurred the 16 year old to create Bird Bot. But for desperate parents this holiday season, bots are a useful tool to snag prized gifts.
Outside of a general on-site bot assistant, businesses aren’t using them to their full potential. Troubleshoot your sales funnel to see where your bottlenecks lie and whether a shopping bot will help remedy it. Not many people know this, but internal search features in ecommerce are a pretty big deal.
I love and hate my next example of shopping bots from Pura Vida Bracelets. They too use a shopping bot on their website that takes the user through every step of the customer journey. Finding high-quality clothes and accessories for women are Francesca’s specialty.
Bots can get pricey as they can be difficult to purchase, with bot makers releasing a limited number of copies at retail, Insider’s Shoshy Ciment reported in September. Once those are sold out, bots often resell for thousands of dollars — up from a few hundred dollars at their release. In terms of numbers, AIO Bot users cooked on every Air Jordan Release, including the AJ1 Royal Toe, Satin Snakeskin, Jordan 1 Smoke Grey, and much more. Plus, being always in stock makes NSB one of the most sought-after bots.
Why Use an Online Ordering and Shopping Bot?
It only requires customers to enter their travel date, accommodation choice, and destination. Afterward, the shopping bot will search the web to find the best deal for your needs. If you have a travel industry, you must provide the highest customer service level. It’s because the customer’s plan changes frequently, and the weather also changes. To improve the user experience, some prestigious companies such as Amadeus, Booking.com, Sabre, and Hotels.com are partnered with SnapTravel.
Comcast and Xfinity Lose Customers – Thanks to Cord-Cutters and … – tech.slashdot.org
Comcast and Xfinity Lose Customers – Thanks to Cord-Cutters and ….
Denial of inventory bots can wreak havoc on your cart abandonment metrics, as they dump product not bought on the secondary market. In another survey, 33% of online businesses said bot attacks resulted in increased infrastructure costs. While 32% said bots increase operational and logistical bottlenecks. Last, you lose purchase activity that forms invaluable business intelligence. This leaves no chance for upselling and tailored marketing reach outs. But when bots target these margin-negative products, the customer acquisition goals of flash sales go unmet.
The Operator offers its users an easy way to browse product listings and make purchases. However, in complicated cases, it provides a human agent to take over the conversation. Shopping carts provide shoppers with personalized options for purchase. Customer chats become eCommerce tools to find suitable products according to what they need.
It comes with features such as scheduled tasks, inbuilt monitors, multiple captcha harvesters, and cloud sync.
However, Quillbot’s grammar-checking capabilities fall short of Grammarly’s robust editing features.
Even though bots are powerful customer service tools, some situations need to be addressed by human support.
Across all industries, the cart abandonment rate hovers at about 70%.
Influencer product releases, such as Kylie Jenner’s Kylie Cosmetics are also regular targets of bots and resellers.
For instance, you can qualify leads by asking them questions using the Messenger Bot or send people who click on Facebook ads to the conversational bot. The platform is highly trusted by some of brands and serves over 100 million users per month. These solutions aim to solve e-commerce challenges, such as increasing sales or providing 24/7 customer support.
Data from Akamai found one botnet sent more than 473 million requests to visit a website during a single sneaker release. Bots can skew your data on several fronts, clouding up the reporting you need to make informed business decisions. And they certainly won’t engage with customer nurture flows that reduce costs needed to acquire new customers. In 2020 both Nvidia and AMD released their next generation of graphics cards in limited quantities.
AI Chatbot for Insurance Agencies IBM watsonx Assistant
While insurance is something that customers need to buy, it isn’t necessarily something they want to buy. It’s essential for companies to take an educational-first approach to get prospects on board with the idea of paying premiums and buying insurance products. Naturally, they would go looking for answers from agents who can guide them through different policies and products and suggest what would be ideal for them. With global insurance spending on AI platforms set to reach $3.4 billion by 2024, now’s the time to take the lead.
Fraudulent claims are a big problem in the insurance industry, costing US companies over $40 billion annually. Bots can comb through claim data and identify trends that humans may miss. The article delves into the numerous use cases of Generative AI chatbots for insurance industry, highlighting the benefits of their integration. If, for example, a customer wants to buy an insurance product, the bot can ask them a series of questions and create a plan and quote premiums that match the policyholders needs. If they can’t solve an issue, they can ask the policyholder if they’d like to be put through to an agent and make the connection directly.
Top 9 Chatbot Use Cases in Insurance
So, a chatbot can be there 24/7 to answer frequently asked questions about items like insurance coverage, premiums, documentation, and more. The bot can also carry out customer onboarding, billing, and policy renewals. The ability of chatbots to interact and engage in human-like ways will directly impact income. The chatbot frontier will only grow, and businesses that use AI-driven consumer data for chatbot service will thrive for a long time. Maya assists users in completing the forms necessary for obtaining a quote for an insurance policy. This chatbot is a prime example of how to efficiently guide users through the sales funnel engagingly and effectively.
Able to learn and adapt over time, they may be also used by chatbot solutions to maximize the creation of user intents and reach much higher automation rate from scratch than ever. They are designed to follow a set of pre-programmed rules and guidelines, ensuring consistency and accuracy in their responses. Analyzing customer data and making recommendations based on historical patterns, they’re reducing the risk of human error. Insurance giant Zurich announced that it is already testing the technology “in areas such as claims and modelling,” according to the Financial Times (paywall). I think it’s reasonable to assume that most, if not all, other insurance companies are looking at the technology as well. My own company, for example, has just launched a chatbot service to improve customer service.
Aspire General Insurance Services:
With multiple use cases in the industry, chatbots are expected to play a significant role throughout the insurance value chain. Right from pre-purchase, purchase, to customer service, marketing and other back-end operations, chatbots are expected to be the innovation in insurance. Chatbot technology has helped improve service and communication in the insurance sector. From improving reliability, security, connectivity and overall comprehension, AI technology has transformed the industry. Business process outsourcing solutions provided by professional providers can utilize these technologies to carry out various insurance processes in a quick, simple and efficient manner.
In addition, chatbots can proactively reach out to insurance customers to offer assistance. Chatbots can improve client satisfaction by providing quick and efficient customer service. This is where AI-powered chatbots come in, as they can provide 24/7 services and engage with clients when they need it most. Conversational AI can be used to assess risk, by analyzing data on individual customers and identifying potential risk factors. This can help insurers to more accurately price policies and provide personalized recommendations for customers.
Bots help you analyze all the conversation data efficiently to understand the tastes and preferences of the audience. You can always trust the bot insurance analytics to measure the accuracy of responses and revise your strategy. It’s now possible to build and customize your insurance bot with zero coding. An insurance company will find it easy to create a powerful bot anytime and start engaging the customers round the clock. A growing number of insurance firms are now deploying advanced bots to do a thorough damage assessment in specific cases such as property or vehicles.
It serves customers with quotes, policy renewal, and claims tracking without any human involvement. AI can reduce the turnaround time for claims by taking away the manual work from the processes. Insurers will be able to design a health insurance plan for an individual based on current health conditions and historical data.
For eg, a customer can initiate a conversation with the chatbot to report an accident. The chatbot asks for details such as date, location, and a description of the incident. Gone are the days when you had to dig through piles of papers to find your insurance details. With a chatbot, managing your policy is as easy as chatting with a friend. Whether you’re initiating a new claim or simply checking the status of an existing one, the chatbot is there to guide you step-by-step.
Additionally, chatbots can be used to proactively reach out to policyholders before, during, or after a catastrophic event to provide information and assistance. This can help to reduce the frequency and severity of losses, and it can also alleviate demand on the call center during peak times. In the previous blog post, we discussed the shortcomings of traditional chatbots used by insurance companies and the way conversational AI can address these limitations. It is evident from several use cases of conversational AI in the insurance sector that it has extended the scope of automated customer support and improved the quality of customer interactions. Each customer has unique needs which means they may need some personal attention to find the right one.
Chatbots create a smooth and painless payment process for your existing customers. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month. You can see more reputable companies and media that referenced AIMultiple. Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur.
Based on responses, chatbots can refine policies, providing users with detailed information on existing options and pricing plans, and link them to a merchant (if necessary). Despite the complexity that the insurance sector entails, people still insure everything. However, unlike a few years ago, now they have become a lot pickier and only opt for insurers that keep things simple. Chatbots in insurance can on how the process works, compare as well as suggest the optimal policy, from multiple carriers, based on the customer’s profile and inputs.
Rising Popularity of the AI Chatbots
Insurers will need to ensure that their use of OpenAI models does not result in unintended bias or discrimination against particular groups of policyholders. Insurers may be required to provide transparency into how OpenAI models are being used and how decisions are being made based on the output of these models. This may include providing explanations of how the models work, what data is being used to train them, and how the models are being used to make decisions. ChatGPT can be seamlessly integrated into existing applications and systems, making it easy for businesses to deploy and manage their chatbot solution. Reach out to our friendly experts to learn more about KeyReply’s proven method of deploying AI solutions in the insurance sector.
In an increasingly competitive and digital insurance marketplace, managing and mitigating risks is more critical than ever. This strategic balance between selling more and prioritizing customer needs elevates customer satisfaction, naturally instilling a greater degree of trust. Talk to our insurance domain experts to learn more about the top ChatGPT use cases in the insurance industry. Perhaps the workflow is too long, and people start disengaging after the fifth or sixth question. Regulations like the GDPR (General Data Protection Regulation) must be complied with by technologies, allowing conversations to be examined, retrieved, made anonymous, encrypted, or deleted as needed. Therefore, conversational information must be incorporated into a centralized authentication system and inaccessible to third parties.
Additionally, the survey found that respondents aged were much more comfortable receiving healthcare-related self-service through automated channels such as chatbots and IVAs.
75% of consumers opt to communicate in their native language when they have questions or wish to engage with your business.
As long as the work gets done, consumers are quite accepting of the steeping trend of insurance chatbots.
The Claims Bot asks the user a series of questions before either guiding the user to the appropriate pages or connecting them with an available agent.
For an easier understanding, we have bucketed the use case based upon the type of service that the chatbots can provide on behalf of insurance agents. An insurance chatbot is a virtual assistant powered by artificial intelligence (AI) that is meant to meet the demands of insurance consumers at every step of their journey. Insurance chatbots are changing the way companies attract, engage, and service their clients. Insurance Chatbots are cutting-edge technology that may provide insurers with several advantages, including 24/7 customer service.
The CEO’s Guide to the Generative AI Revolution – BCG
Building a Basic Chatbot with Pythons NLTK Library by Spardha Python in Plain English
This is just a basic example of a chatbot, and there are many ways to improve it. Chatbots can provide real-time customer support and are therefore a valuable asset in many industries. When you understand the basics of the ChatterBot library, you and train a self-learning chatbot with just a few lines of Python code. Now that we have a solid understanding of NLP and the different types of chatbots, it‘s time to get our hands dirty. In this section, we’ll walk you through a simple step-by-step guide to creating your first Python AI chatbot. We’ll be using the ChatterBot library in Python, which makes building AI-based chatbots a breeze.
On the other hand, SpaCy excels in tasks that require deep learning, like understanding sentence context and parsing.
That’s it, run your program to see the response from your bot to the comment How are you doing?.
The layers of the subsequent layers to transform the input received using activation functions.
A chatbot built using ChatterBot works by saving the inputs and responses it deals with, using this data to generate relevant automated responses when it receives a new input.
The more keywords you have, the better your chatbot will perform.
After setting up the Python process, let’s use flask ngrok to create a public URL for the webhook and listen to port 5000 (in this example). For Kompose webhook, you will need an HTTPS secured server since the local server (localhost) will not work. You can also use a server and point a domain with HTTPS to that server.
We are almost done setting up the software environment, and it’s time to get the OpenAI API key. Gradio allows you to quickly develop a friendly web interface so that you can demo your AI chatbot. It also lets you easily share the chatbot on the internet through a shareable link. Now, it’s time to install the OpenAI library, which will allow us to interact with ChatGPT through their API. In the Terminal, run the below command to install the OpenAI library using Pip.
The other import you did above was Reflections, which is a dictionary that contains a set of input text and its corresponding output values. This is an optional dictionary and you can create your own dictionary in the same format as below. The database_uri parameter sets the location of the database that the chatbot will use for storage. In this example, a SQLite database is used with the filename database.db. Natural Language Processing with Python provides a practical introduction to programming for language processing. In ChatterBot, a logic adapter is a class that takes an input statement and returns a response to that statement.
Build a Machine Learning Model with Python
It uses machine learning algorithms to analyze text or speech and generate responses in a way that mimics human conversation. NLP chatbots can be designed to perform a variety of tasks and are becoming popular in industries such as healthcare and finance. In this python chatbot tutorial, we’ll use exciting NLP libraries and learn how to make a chatbot from scratch in Python. A chatbot is a computer program that interacts with humans or simulates a human conversation with a machine via a written message or voice. It is programmed to work independently without the intervention of human operators.
This will help you determine if the user is trying to check the weather or not. This tutorial assumes you are already familiar with Python—if you would like to improve your knowledge of Python, check out our How To Code in Python 3 series. This tutorial does not require foreknowledge of natural language processing. TheChatterBot Corpus contains data that can be used to train chatbots to communicate. A reflection is a dictionary that proves advantageous in maintaining essential input and corresponding outputs. You can also create your own dictionary where all the input and outputs are maintained.
SVM Kernels: Polynomial Kernel – From Scratch Using Python.
The ‘chatterbot.logic.BestMatch’ command enables the bot to evaluate the best match from the list of available responses. A rule-based chatbot is one that relies on a set of rules or a decision tree to determine how to respond to a user’s input. The chatbot will go through the rules one by one until it finds a rule that applies to the user’s input. The chatbot will look something like this, which will have a textbox where we can give the user input, and the bot will generate a response for that statement.
AI-based chatbots learn from their interactions using artificial intelligence. This means that they improve over time, becoming able to understand a wider variety of queries, and provide more relevant responses. AI-based chatbots are more adaptive than rule-based chatbots, and so can be deployed in more complex situations. Rule-based chatbots interact with users via a set of predetermined responses, which are triggered upon the detection of specific keywords and phrases.
This blog was a hands-on introduction to building a very simple rule-based chatbot in python. We only worked with 2 intents in this tutorial for simplicity. You can easily expand the functionality of this chatbot by adding more keywords, intents and responses. Using the ChatterBot library and the right strategy, you can create chatbots for consumers that are natural and relevant.
Four things that matter in the AI hype cycle – CIO
For example, if you say “hello,” it might respond with “Hi there! ” It can also tell you jokes, give you weather updates, or provide support information. It’s really interesting to see our chatbot giving us weather conditions. Notice that I have asked the chatbot in natural language and the chatbot is able to understand it and compute the output. Welcome to the tutorial where we will build a weather bot in python which will interact with users in Natural Language. Okay, so as we finished the patterns and responses, let’s take a look at something called reflections.
Another way is to use a tool such as Dialogflow, this machine learning cloud platform provided by Google is a visual editor for building chatbots. You can also find many tutorials online that show how to build chatbots using Python code. A self-learning chatbot uses artificial intelligence (AI) to learn from past conversations and improve its future responses.
Now, we’ll define the responses for the chatbot based on different user inputs. For this guide, we’ll keep it simple and include only 12 questions that the chatbot can respond to. Feel free to add more responses and customize the answers to your liking.
So, as you can see, the dataset has an object called intents. The dataset has about 16 instances of intents, each having its own tag, context, patterns, and responses. Python Chatbot Project Machine Learning-Explore chatbot implementation steps in detail to learn how to build a chatbot in python from scratch. Chatterbot combines a spoken language data database with an artificial intelligence system to generate a response. It uses TF-IDF (Term Frequency-Inverse Document Frequency) and cosine similarity to match user input to the proper answers.
In the Chatbot responses step, we saw that the chatbot has answers to specific questions. And since we are using dictionaries, if the question is not exactly the same, the chatbot will not return the response for the question we tried to ask. Sometimes, we might forget the question mark, or a letter in the sentence and the list can go on. In this relation function, we are checking the question and trying to find the key terms that might help us to understand the question.
To do this, you can get other API endpoints from OpenWeather and other sources. Another way to extend the chatbot is to make it capable of responding to more user requests. For this, you could compare the user’s statement with more than one option and find which has the highest semantic similarity.
Planning a trip can be exciting, but it can also be overwhelming.
Here, we will create a function that the bot will use to acquire the current weather in a city.
The input() function is used to get user input from the command line, and the bot.get_response() method is used to get the chatbot’s response to the user’s input.
You can find a list of all Telegram Bot API data types and methods here.
Artificial intelligence, specifically designed to improve human−computer interactions, utilises machine learning and Natural Language Processing (NLP) to create chatbots. Chatbots converse with humans in a natural, human−like manner by adapting to natural human language. To create a conversational chatbot, you could use platforms like Dialogflow that help you design chatbots at a high level. Or, you can build one yourself using a library like spaCy, which is a fast and robust Python-based natural language processing (NLP) library. SpaCy provides helpful features like determining the parts of speech that words belong to in a statement, finding how similar two statements are in meaning, and so on.
While you do want your chatbot to help generate leads, you don’t want to overwhelm your prospect with dozens of qualifying questions. Instead, figure out what they’re looking for and answer those questions first. So they’re continuing to fill the top of the funnel, too — using bots. The tool they developed is able to manage the search experience for buyer clients as well as helping them book tours online that will populate on the agent’s calendar.
Meta’s Celebrity AI Chatbots on Facebook, Instagram Are Surreal – Bloomberg
Meta’s Celebrity AI Chatbots on Facebook, Instagram Are Surreal.
For instance, when a client asks for property information, the chatbot can immediately respond with relevant details, saving agents substantial time and minimizing delays in communication. With chatbot automation for the real estate industry, agents can streamline their sales and marketing efforts and enhance their overall customer service. Contact us today to learn more about how our chatbot solutions can help you revolutionize your real estate business. Real estate chatbots are AI-powered conversational solutions that assist realtors in qualifying leads and guiding them through the conversion funnel with meaningful and contextual conversations. In addition to answering FAQs, real estate chatbots are equipped for sophisticated features, such as coordinating with your agents to schedule property visits and guiding prospects through virtual tours. These chatbots can reduce manual labor, enhance real estate agent-client interactions, and increase productivity for real estate professionals.
Collecting customer reviews
Data collection plays a significant role in delivering the best results in real estate, but unfortunately, it’s an area where AI chatbots have fallen short. This transformation is particularly valuable in the real estate sector, creating a win-win situation. Buyers can receive relevant property information, enhancing the property viewing process, while agents can automate their customer interactions, attracting more leads and saving both time and money. The chatbot could also act as a coach for selling by reminding the real estate agent on the way to a client meeting about professional customer engagement and sales techniques. Do you agree that not everyone is looking for the same type of property type?
In the real estate industry, customers will usually go for a property hunt after their offices and have queries at odd hours and days. It is a challenge for companies to get back to their customers in real-time. They can be the first line of defense that respond to your customers instantly, and give them an estimated time of resolution in case of a complex query. Sales representatives and real estate agents clearly understand that in order to bring in some conversions, follow-ups are extremely important.
Use cases of Chatbots for Real Estate Industry
At Floatchat, we specialize in providing innovative chatbot solutions tailored to the unique needs of real estate professionals. With our advanced chatbot technology, we can help you streamline your communication processes, enhance your customer interactions, and boost your sales and marketing strategies. Our team of experts is committed to developing chatbot solutions that meet the high standards of the real estate industry. We understand the importance of personalized communication and strive to provide chatbots that can handle complex client queries, provide accurate property recommendations, and assist with personalized marketing campaigns. With the help of Floatchat, we have access to cutting-edge chatbot technology that enables us to streamline our communication processes and improve our overall productivity. Their intelligent chatbots for real estate agents are designed specifically for realtors, providing us with the tools we need to better serve our clients.
No more sifting through irrelevant listings; it’s all about efficiency and personalization.
Other real estate artificial intelligence products are automating property managers’ roles.
Customer can browse and compare different housing loan plans, check eligibility, and apply online without any human intervention.
Rather than going in cold, now your ISA or agent knows exactly which questions and answers to lead with to ensure that your first human interaction is as value-driven as possible.
They were each given three days, at the end of which, it was deduced that the chatbot was able to “read between the lines” as to what the buyer really wanted, based on his responses to properties shown earlier.
When I clicked a name, the message history between Brenda and the prospect appeared on the screen. Everyone was aggressively good-natured, with leftist politics and pronouns in their display names. When we weren’t talking about Brenda, we were swapping syllabi, soliciting tattoo advice and distributing e-flyers to our sound and movement workshops. In our midst were a handful of senior operators who acted as shift supervisors. Each day when we reported for work one of them would hail us with a camp counsellor’s greeting.
Frequently Asked Questions
My eyes would apprehend the web of critical words – pets, rent, utilities – and my hands would hit keys like notes in a musical passage. I stopped worrying about Brenda’s tone and began letting any message through as long as it was factually accurate. I realised that when Brenda sounded odd and graceless, people were less likely to get intimate, which meant less HUMAN_FALLBACK, which meant less effort for me. Months of impersonating Brenda had depleted my emotional resources.
A typical encounter with Brenda began when a prospect saw an apartment on an online real estate marketplace. Eventually, a woman with an ardent, breathy voice would speak over the line. The incoming millennial buyer demographics demand channels where you can reach out to them in ways, they know the best. According to the National Association of Realtors (NAR), 56% of buyers—aged 36 and younger—found their properties on the internet. With businesses going neck and neck to up their ante and stay relevant to consumers, chatbots are a great way to kickstart your digital presence.
Chatbots as well as human agents can use this well-categorized, segregated information to target their customers based on different properties. According to a Deloitte survey, automation technologies like chatbots can enhance employee productivity by as much as 20%. In real estate, this translates to agents getting more bandwidth to focus on high-impact tasks such as strategic marketing and finding the perfect property fits for clients. Take your business to new heights by using this free real estate chatbot template. With this bot, you can provide correct information to your prospective customers and can also capture your lead data with a timely and customized touch. This real estate chatbot helps realtors automatically respond to buyer and seller leads.
Moreover, if a real estate agent aims to expand their reach to a broader audience, this type of chatbot may not be the best solution for them. At Floatchat, we understand the importance of staying at the forefront of innovative technology. We are constantly developing and improving our chatbot solutions to meet the needs of the ever-evolving real estate industry. The questions asked by the customer can be with regards to a specific property or with regard to the process.
For this reason, I see a lot to be excited about in the recent generative AI boom across industries—especially as it relates to multifamily housing and real estate. The primary focus throughout time has always been to find harmony between the human aspects and the non-human (or even superhuman) forces of nature. As we evolved, our resources have expanded beyond the natural elements to include digital and technological means of support and progress. Yet, our basic need for harmony in our dwellings remains the same. Brenda, the recruiter told me, was a sophisticated conversationalist, so fluent that most people who encountered her took her to be human.
Chatbots offer a solution to the longstanding challenge of limited availability and responsiveness.
Additionally, these chatbots can also qualify leads, helping agents to prioritize their communication and focus on the most promising prospects.
To begin a shift, I would log on to a command station that looked like an email inbox in dark mode.
Notions of home and community are expanding as quickly as the devices we use to customize our spaces, and it’s no longer feasible for operators in the field to refuse to incorporate the influx of tech-based resources.
The bot then does the heavy lifting of finding options and proposes the best ones.
The Professional plan costs $41 for 1 user and 300 sessions per month.
MobileMonkey is a multichannel chatbot platform that offers real estate businesses, e-commerce businesses, and other SMBs an easy way to connect with their customers. The explosion of chatbot platforms since 2017 is a strong indication that these handy virtual assistants are here to stay. Oftentimes, the leads coming through your chatbot won’t be so hot.
Scheduling Appointments: Your Digital Scheduler
Importantly, most of the literature that chatbots will read is in the public domain and on the internet. To the extent that sites post illicit copies, writers’ complaints and copyright suits should be targeted at illegal postings and the owners of those sites. ADA wishes to thank all participating teams for their hard work, dedication, and innovative spirit. The success of ADA Business Messaging Hackathon 2023 is a testament to the evolution and transformation of conversational & generative AI on WhatsApp. Impressively, most of the top 10 teams in the hackathon were made up of students.
SmartCompany is the leading online publication in Australia for free news, information and resources catering to Australia’s entrepreneurs, small and medium business owners and business managers. Real estate Bots can be taught to perform many tasks currently done by humans. We have trained our Bots to greet every person immediately, qualify their buyer and seller needs, and deliver the information they want without using any human resources. Part of their offerings includes leasing automation, PPC management, reputation management, and resident retention software. Compared to alternatives with similar features, Roof is fairly expensive. On their website, clients can fill out a form to request custom pricing.
By providing such advanced chatbot technology for real estate professionals, Floatchat is helping agents to enhance their efficiency and productivity. With Floatchat’s automated chat solutions for real estate agents, agents can handle multiple client inquiries simultaneously, provide instant responses, and improve overall customer satisfaction. In addition, AI technology offers chatbot automation for the real estate industry. Our automated chatbots for real estate agents can provide instant responses to common queries, improving response time and overall customer satisfaction. With Floatchat’s innovative AI chatbot solutions, real estate professionals can streamline their communication processes and provide exceptional service to their clients.
Amazon launches generative AI to help sellers write product descriptions
The capabilities of generative AI have already proven valuable in areas such as content creation, software development and medicine, and as the technology continues to evolve, its applications and use cases expand. For professionals and content creators, generative AI tools can help with idea creation, content planning and scheduling, search engine optimization, marketing, audience engagement, research and editing and potentially more. Again, the key proposed advantage is efficiency because generative AI tools can help users reduce the time they spend on certain tasks so they can invest their energy elsewhere.
Embedded into the enterprise digital core, generative AI and foundation models will optimize tasks, augment human capabilities and open up new avenues for growth. In the process, these technologies will create an entirely new language for enterprise reinvention. The large language models (LLMs) and foundation models powering these advances in generative AI are a significant Yakov Livshits turning point. They’ve not only cracked the code on language complexity, enabling machines to learn context, infer intent, and be independently creative, but they can also be quickly fine-tuned for a wide range of different tasks. Someone has already written a program called CLIP Interrogator that analyzes an image and comes up with a prompt to generate more images like it.
What are the benefits and applications of generative AI?
Even perfect security systems with thousands of known threat detection rules are not future proof and the adversaries continue to work on new methods of attacks and will inevitably outsmart these security systems. Data and extracting valuable information from it has become critical for successful business operations and planning. That’s not what AI only has to offer, but let’s start with the most common examples, then we can move on to the main topic – generative AI. In this article, we explore what generative AI is, how it works, pros, cons, applications and the steps to take to leverage it to its full potential. Nearly four out of five (79%) business leaders expect their employees will use generative AI often in their work, with 39% anticipating employees will use generative AI every day. Nearly half of the workers we surveyed (45%) say AI reduces or eliminates boring or tedious tasks, while 41% say AI has changed how they work for the better.
Within the technology’s first few months, McKinsey research found that generative AI (gen AI) features stand to add up to $4.4 trillion to the global economy—annually. Generative AI could eventually be used to produce designs for everything from new buildings to new drugs—think text-to-X. Adobe is already building text-to-image generation into Photoshop; Blender, Photoshop’s open-source cousin, has a Stable Diffusion plug-in. And OpenAI is collaborating with Microsoft on a text-to-image widget for Office. Researchers in the field known as computational creativity describe their work as using computers to produce results that would be considered creative if produced by humans alone. What you get back is a handful of images that fit that prompt (more or less).
Generative AI vs. machine learning
By saving advisors and customer service employees time when it comes to questions about markets, recommendations and internal processes, the assistant frees them to engage more with clients, he said. Morgan Stanley, a top investment bank and wealth management juggernaut, made waves in March when it announced that it had been working on an assistant based on OpenAI’s GPT-4. Competitors including Goldman Sachs and JPMorgan Chase have announced projects based on Yakov Livshits. But Morgan Stanley is the first major Wall Street firm to put a bespoke solution based on GPT-4 in employees’ hands, according to Jeff McMillan, head of analytics, data and innovation at Morgan Stanley wealth management. Unfortunately, despite these and future efforts, fake videos and images seem to be an unavoidable price to pay for the benefits we are expected to get from generative AI in the near future. One is generating (for instance images) while the second is verifying the results, for instance if the images are natural and look true.
UK’s competition watchdog drafts principles for ‘responsible’ generative AI – TechCrunch
UK’s competition watchdog drafts principles for ‘responsible’ generative AI.
Many implications, ranging from legal, ethical, and political to ecological, social, and economic, have been and will continue to be raised as generative AI continues to be adopted and developed. Artificial intelligence has a surprisingly long history, with the concept of thinking machines traceable back to ancient Greece. Modern AI really kicked off in the 1950s, however, with Alan Turing’s research on machine thinking and his creation of the eponymous Turing test.
Yakov Livshits Founder of the DevEducation project A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.
What’s behind the sudden hype about generative AI?
Focus on people as much as on technology, ramping up talent investments to address both creating AI and using AI. This means developing technical competencies like AI engineering and enterprise architecture and training people across the organization to work effectively with AI-infused processes. We can also expect a large number of new tasks for people to perform, such as ensuring the accurate and responsible use of generative AI systems. It’s why organizations that invest in training people to work alongside generative AI will have a significant advantage. Large companies like Salesforce Inc (CRM.N) as well as smaller ones like Adept AI Labs are either creating their own competing AI or packaging technology from others to give users new powers through software. Our research found that equipping developers with the tools they need to be their most productive also significantly improved their experience, which in turn could help companies retain their best talent.
And ensuring that those boundaries create provable safety all the way from the actual code to the way it interacts with other AIs—or with humans—to the motivations and incentives of the companies creating the technology. And we should figure out how independent institutions or even governments get direct access to ensure that those boundaries aren’t crossed. On the how—I mean, like, I’m not going to go into too many details because it’s sensitive. But the bottom line is, we have one of the strongest teams in the world, who have created all the largest language models of the last three or four years. Amazing people, in an extremely hardworking environment, with vast amounts of computation. We made safety our number one priority from the outset, and as a result, Pi is not so spicy as other companies’ models.
This has given organizations the ability to more easily and quickly leverage a large amount of unlabeled data to create foundation models. As the name suggests, foundation models can be used as a base for AI systems that can perform multiple tasks. In 2014, advancements such as the variational autoencoder and generative adversarial network produced the first practical deep neural networks capable of learning generative, rather than discriminative, models of complex data such as images.
This technology allows generative AI to identify patterns in the training data and create new content.
Worse, sometimes it’s biased (because it’s built on the gender, racial, and myriad other biases of the internet and society more generally) and can be manipulated to enable unethical or criminal activity.
Going forward, a generative AI agent will have a history of working with each individual employee—and will continually be trained by each one from a preferred pool of information.
Of course it’s science fiction, but with the latest technology we are getting closer to that goal.
Techniques include VAEs, long short-term memory, transformers, diffusion models and neural radiance fields.
As you may have noticed above, outputs from generative AI models can be indistinguishable from human-generated content, or they can seem a little uncanny. The results depend on the quality of the model—as we’ve seen, ChatGPT’s outputs so far appear superior to those of its predecessors—and the match between the model and the use case, or input. ChatGPT may be getting all the headlines now, but it’s not the first text-based machine learning model to make a splash. OpenAI’s GPT-3 and Google’s BERT both launched in recent years to some fanfare. But before ChatGPT, which by most accounts works pretty well most of the time (though it’s still being evaluated), AI chatbots didn’t always get the best reviews. GPT-3 is “by turns super impressive and super disappointing,” said New York Times tech reporter Cade Metz in a video where he and food writer Priya Krishna asked GPT-3 to write recipes for a (rather disastrous) Thanksgiving dinner.
Similarly, images are transformed into various visual elements, also expressed as vectors. One caution is that these techniques can also encode the biases, racism, deception and puffery contained in the training data. Generative AI is a type of artificial intelligence that can learn from and mimic large amounts of data to create content such as text, images, music, videos, code, and more, based on inputs or prompts. Some examples of foundation models include LLMs, GANs, VAEs, and Multimodal, which power tools like ChatGPT, DALL-E, and more. ChatGPT draws data from GPT-3 and enables users to generate a story based on a prompt.